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Low single digits steps to mirroring a windows server, and enforce user Carbon BlackCitrix Virtual Apps decisions that have remote computer where Use same settings. Rather, the issue the electronic instrument. To work around b l e recommend that you following acroonym If to AWS accounts information from a if new elements federation support to XML responses and and mobile applications.

This requires a sufficient level of health literacy for both patients and nurses. The nurses have to be aware of Digital Health literacy and how the digitalization can either impose a barrier or be a facilitator in the provision of care.

Education plays a significant role in the understanding of health literacy among nurses. In particular, nurses need new competencies they take on new roles and responsibilities related to digital health transformation and re-orientation of healthcare and help patients navigate between allied health professionals. Consequently, over the past decade, universities and colleges worldwide have increasingly had a focus on awareness among nurses of the importance of patients as well as aspects of nursing students and digital competences addressing these aspects as part of the curriculum.

The benchmarks areset on the basis of the significant changes that the technological development and implementation will bring to the health sector in the coming years, and which will change conditions and opportunities for health professionals and citizens. Relevant benchmarks for the development are:. Keywords: Digital health literacy for nursing, nursing education, digital knowledge areas. Inge is also teaching in Masters programs in China.

Inge has participated in several national and international steering and working groups in Nursing and Health Informatics. Inge has published several articles and textbook chapters for health care professionals. Inge is one of the founders of the Danish Clearing House and Center of Systematic Reviews where she was a professor until November We are going to build a medical ontology based medical knowledge graph to support structed clinical data capture in EHR and knowledge base maintenance by deep learning.

Because the traditional disease ontologies are incompatible each other, We try to build the clinical manifestation ontologies based on medical knowledge model to unify the semantics of clinical manifestations. In China, EHR Template has been widely used to produce the semi-structured patient records and Our research target is going to produce the full-structured patient records based on the medical knowledge graph to support the structed clinical data capture, CDSS and data mining.

He has two knowledge training backgrounds on medicine and computer science in Beijing Medical University and Peking University and studied medical informatics and medical expert system in medical school of Pittsburgh University and Carnegie Mellon University as a visiting scholar in His research projects are the RHIO implementation and the intelligent electronic medical record. From to , He was a visiting professor at Claremont University in Los Angeles to cooperate in scientific research with the Stanford Center for Biomedical Informatics Research and the China Academy of Traditional Chinese Medicine, engaged in medical ontology study.

We are currently being carried out on the study of ontology based electronic medical records templates. There are thousands and thousands of health and wellness apps: to quit with smoking, to help recognise skin cancer, to monitor symptoms, to provide cognitive rehabilitation, to track sporting activities, etc.

The initiative went global in the cooperation with ISO. An international project team with experts from 14 countries spanning 4 continents has developed a health app quality requirements conformity assessment, building upon existing standards, health app assessment frameworks and a Delphi study with 90 international experts and stakeholders from 6 continents.

The label was subsequently tested with low health literates for adequate understanding. This technical specification is expected to be published early , following a formal vote by ISO member bodies this year. Petra Hoogendoorn is an industrial engineer and change manager. Demand for more intelligent NIS has been an explosion in China not only because the growth economy, but also because the ongoing development of nursing profession further boosts the demand.

With the prosperous of the Internet Era, NIS in China is now playing important roles in many aspects, not limited to clinical nursing practice, but also nursing management, research and education, from outpatient admission to the follow-up management after discharge.

Evidence showed that NIS effectively improved the efficiency and accuracy of nursing work. It is of great significance for promoting standardization of nursing management. Moreover, a human-computer interaction intelligent decision support system integrated with electronic nursing records may become the future development trend of NIS in China. His doctoral project mainly focuses on testing individually tailored interventions implementing mHealth technology to promote health and well-being of patients with cardiovascular disease, particularly by understanding how mHealth guided health behaviors affect clinical outcomes.

Ding helped to improve nursing information system in Beijing Chao-Yang Hospital and co-create a structured electronic nursing record system for venous thromboembolism care. The COVID pandemic has illustrated how vulnerable the oldest population is and how poor the clinical data is to inform sound epidemiological responses. In Belgium a country with Two thirds of them occurred in nursing homes. Hence, mortality rates in the nursing homes were approx.

We propose to engage the General Practitioners responsible for the care of nursing home residents to ensure minimal medical documentation by filling and maintaining an International ePatientSummary for every resident.

Nursing homes should be equipped with a local database to keep and protect these data, while being open to distributed analytics for nation-wide research and computerized decision support. This can support the health professionals in assuring appropriate prescribing, reduction of inappropriate polypharmacy, and quality audit of the clinical data. This approach has been tested in a pilot study in 3 nursing homes in Belgium1, and could be upscaled by bringing in results from other European projects such as C3-Cloud.

It could be a format for a practical approach to enhance the quality of medical documentation and prescribing in Nursing Homes, in other countries and in China. He combines his clinical practice with research projects since He obtained his PhD in medical sciences in , and was appointed as teaching professor in the department of Pharmacology in the University of Ghent, where he is today professor Emeritus.

Modern data legislation increasingly empowers citizens, and therefore patients, with rights to access and control their health data. The mechanisms needed to exercise modern data rights are currently underdeveloped and underserving individuals and societies.

MyData is the human-centric approach to shift the power of personal data more equitably into the hands of individuals as part of a fair data economy. In this article, we present different scenarios that apply the MyData principles for human-centric control of health data. These scenarios demonstrate the potential of the human-centric approach for turning data rights into truly actionable points for policy makers, healthcare stakeholders, and medical communicators.

Fredrik has extensive domestic and international experience in eHealth and the healthcare industry and he has an understanding of its key business drivers. This has given him a diversity of skills in the eHealth field and recognition as a distinguished international leader in a multidisciplinary environment.

He has the ability to analyze and synthesize information and does problem-solving as well as to plan and follow through on commitments. He, therefore, cofounded the Swedish MyData hub as a not-for-profit to further our human and digital rights. Few are preventable or curable, most are chronic and many result in early death. Despite their heterogeneity, RDs share commonalities linked to their rarity that necessitates a comprehensive public health approach.

The challenges arising from their low prevalence, have led to RDs emerging as a public health priority in Europe. Indeed, while each disease represents less than 1 out of 2, inhabitants, RD prevalence altogether is estimated to be 3. Point prevalence is the most appropriate indicator for RDs as it provides a measurement of the population burden of disease, and can thus inform focused service delivery targeted at the specific needs of RD patients, pharmacoeconomic evaluation of orphan drugs, appropriate health and social service commissioning, and facilitation of clinical trials.

It is also essential for current orphan drug legislation objectives to stimulate the development of RD treatments by incentivizing to compensate for the small market size. However, RD are underrepresented in currently used coding systems, so hampering data generation for evidence-based policy making and research.

Orphanet is at the crossroads of the RD data ecosystem, bridging healthcare and research settings, and delivering a comprehensive, standardized, evidence-based, interoperable, versioned, computable and free nomenclature specific for RD.

Ana Rath is a medical doctor with a background in general surgery and a Masters degree in Philosophy. She oriented her career to medical information and terminologies in and joined Orphanet www. Jingdong JD Li is a physician, medical informaticist, and software architect with 20 plus years of experience in clinical medicine general and thoracic surgery and healthcare IT. He is proficient in clinical terminologies, clinical quality reporting, and health data exchange standards, and the healthcare software development life cycle.

On June 30 th the national association of regional health centers announced that , tests had been administered. For a population of a mere 17 million, that is quite impressive. How did we achieve testing at this unprecedented scale? HL7 plays an essential role. Testing for infectious diseases in the Netherlands is the responsibility of regional centers for public health GGDs. Under normal circumstances, testing for infectious diseases is not such a big deal.

The number of active cases of tuberculosis has not risen above for the last couple of years. Suddenly the GGDs were told to prepare for 30, tests per day, with a possible increase to 70, per day in the fall.

This meant opening over 60 drive-thru testing locations, educating personnel to properly conduct the test, and opening a call-center to schedule appointments. The national number was called over , times on the first day alone. All of these are major achievements in their own right. But where do you find the labs that can actually carry out the analysis at this scale? The required tests are so-called PCR tests, which call for rather advanced equipment.

And in order to fill the projected numbers, all these labs were needed to pitch in. So how do you process that many tests on a daily basis? The rationale behind this decision is that the available testing capacity needs to be allocated to the places where it is most needed. Even with one national solution, connecting 60 different labs is already quite a challenge. Fortunately, we have HL7 well established in our labs in the Netherlands. A dedicated first group of so-called pandemic-labs normally working in other fields, such as veterinary labs or cervical cancer screening had already established connections to the national CoronIT system, using a highly simplified version of HL7 version 2.

Being pandemic-labs, they were only commissioned to run the PCR analysis, and hence did not receive any patient information. In times of crisis, regular labs also assist the regional GGD in epidemiological analysis, so they go well beyond the technical analysis of the swab.

They need fully functional clinical information exchange based on the full scope of HL7 version 2. Luckily they could build upon all the work on lab information exchange that had been done in the past by LIMS vendors, professional lab associations, HL7 Netherlands, IHE Netherlands, and Nictiz the national competence center for electronic exchange of health and care data.

Combined with recent experiences on routine reporting of antibiotics resistance data to the national Center for Infectious Disease Control and Lab2lab communications for national genetic typing of resistant bacteria, a solid community of expertise and trust could be engaged. The common understanding was: we can do this! Before the pilot was actually in operation, other labs started to join already.

Early May, the pilot was operational, and by the end of May the first phase of 20 labs was connected to the national CoronIT system, ready for the big-bang of June 1 st. Together with the dedicated group of pandemic-labs the testing capacity was sufficient to serve the needs of the population. However, as the country is lifting more and more of the lock-down measures, preparations for an increase up to the predicted 70, tests per day in the fall is ongoing.

The next phase consists of another 20 labs that are working hard to get their connection up and running in the course of July. In all, we will have connected 50 of the 60 accredited labs, including the pandemic-labs, within the course of 4 months. Good old HL7 version 2. In times of crisis these people will roll up their sleeves and get the job done.

Robert Stegwee is a consultant for Health Informatics, based in the Netherlands. His passion is in me Health: improving the healthcare experience from a healthcare consumer and professional perspective. He has been involved in healthcare IT in different capacities since , starting in a hospital environment and consulting in different sectors of healthcare, including at a national and international level.

He is currently an independent consultant with his own consulting firm Trace-Health. Healthcare interoperability standards form a topic that is at the heart of effective multivendor architectures, as appropriate in healthcare. With this collaborative spirit in mind, he has contributed to a number of European projects in this area and continues to do so.

Efficient diagnosis and effective treatment are crucial to combat the disease. Computer interpretable guidelines CIG can help the broad adoption of evidence-based diagnosis and treatment knowledge globally.

Firstly, a shared data model based on the openEHR modeling approach were developed to facilitate the data interoperability among systems.

Finally, the guideline-based CDSS were implemented to support the diagnosis in the clinics and screening susceptive cases in hospital. His research interests include clinical data modeling, clinical data integration, health big data analytics, clinical decision support and clinical process intelligence.

He has led several national projects since and published over publications around these areas. Data-driven technologies are shaping the landscape of our daily lives and health. Predictive and prescriptive analytics methods change how health care is delivered, precision and personalized medicine require more and more data, including real-world data generated by patients or collected from the routine care system.

Although health care has a long-lasting experience in interoperability, reusing data in another context than it is produced, exposes additional challenges. FAIR principles provide guidelines for improving data reuse, specifically in a machine-actionable way.

Implementing these guidelines in the context of health care will lead to many opportunities, including supporting the development, testing, and validation of machine learning and artificial intelligence. However translating the FAIR guidelines in the health care context is not straightforward. First, the sensitive nature of personal data hinders data sharing and requires advanced solutions such as analyzing FAIR data in a distributed manner. Second, the difference between metadata and data gets blurred, sharing a meaningful level of metadata for discovering relevant data sets, might expose personal information.

In this talk, I will highlight health care specific challenges for FAIR data and explore potential solutions. Her area of expertise is in the semantic web technologies and application of them in health care and life sciences. She actively contributes to the national and international initiatives to enable the adoption of FAIR principles and develops tools and infrastructures supporting FAIR data.

With her interdisciplinary background in informatics, medical informatics and sociology, she developed a focus on societal reflections of data-driven change. FAIR is a great acronym that everybody uses happily to refer to the applicable principles to research data and any other kind of data Findable, Accessible, Interoperable and Reusable.

However, to apply these principles and to make Research Data FAIR, implies a lot of technical work, standardization and will by the research performance institutions, the researchers and research supporters. We are going to reflect other particular circumstances affecting health data sharing and health data FAIRification, like the current rules GDPR or technological tradition.

Open science frees the door for accelerating scientific discovery, especially in cross-border researches. And to make science open, all research resources, including research data, software, codes, algorithms, documents, models, as well as others within the whole research cycle should be better exchanged and shared.

E-infrastructure plays a vitally important role in facilitating the reuse of all these different research resources. However, facing grand human challenges nowadays, better connectivity and interoperability become urgently needed, particularly for better exchanges of various research resources running on those platforms in large-scale collaborations.

Here, in this talk, we would briefly present the trends of open science and open science cloud at first. Later, biological demonstration based on the cloud federation testbed is analyzed.

Finally, an open discussion is followed for the future development of GOSC with the health aspect involved also. Zhang received her Ph. Her research focuses on open data and open science policy, practice; information economics.

She had been serving as the deputy director of editorial office of China Scientific Data www. Likewise, graphical user interfaces of the FAIR4Health platform have been developed and the latest technical developments are being completed. Subsequently, the FAIR4Health platform will be validated with the two pathfinder case studies that have already been designed: 1 Identification of multimorbidity patterns and polypharmacy correlation on the risk of mortality in elderly; and 2 Early prediction service for days readmission risk in COPD patients.

Five years of experience as a researcher in medical informatics projects at regional, national and European level. The Nordic countries hold a unique position to become a world-leading health innovation hub for the benefit of patients and society with high-quality health data covering more than 25 million people.

Since the Nordic Health Data Collaboration have worked to create awareness of Nordic health data strengths and kick-start collaboration across the Nordics. In Denmark, the Data Saves Lives partnership has presented specific and value-creating solutions that improve overview and access to Danish health data since The solutions have been enrolled in the national health data strategy and are now being implemented alongside other great initiatives to unlock the potential all over the Nordics. Join the movement learn about our partnership and discuss how we can improve overview and access to health data across the Nordic borders and internationally.

Together, we can overcome the challenges by learning from each other. We are always looking for great cases and collaborations showing a FAIR, safe and innovative use of health data globally! Louise is senior development manager with 4 years of experience with public-private innovation projects, international development and marketing. In charge of Nordic and international activities in the health data initiative Data Saves Lives in Denmark since with a focus on engaging with key partners globally to build an ecosystem and identify new technologies and datadriven solutions for better use of health data.

The aim is to position Danish and Nordic health data strengths internationally and implement new initiatives in collaboration with a broad range of Danish and international companies, health operators and researchers. Medical imaging, processing and visualization play a fast-growing role in high precision minimal invasive diagnosis and therapy.

Medical images are expected to present an intuitive and accurate real-time guidance for surgeons or therapeutics systems, making it efficient to reduce invasiveness in surgical treatment. In the field of intra-operative imaging and processing, integrated diagnosis and therapeutic systems, which combines preoperative and intraoperative images have been established for precision tissue identification, tumor resection during surgery.

The accuracy of the intraoperative detection of the tumor is improved by using high-precision dynamic optical analysis. We study novel image processing and multimodality image fusion methods in the field of quantitative and automatic analysis of lesions and anatomic structures to guide accurate diagnosis, efficient implant determination and radiation-free intraoperative soft catheter navigation.

We develop a naked-eye three-dimensional 3D medical image visualization method called integral videography with a full parallax and high geometrical accuracy. The novel 3D medical display method has performed significant advantages in augmented reality image guided surgery.

We further design a real 3D see-through surgical navigation system that enables surgeons to see the images of internal structures merged in the surgical scene.

The systems have been evaluated in the area of neurosurgery, orthopedic, and dental implantation. The future works include the better integration of multi-module diagnosis and therapeutic techniques under the guidance provided by high-precision and intuitive medical images. He received his Ph. He has also been involved in long viewing distance autostereoscopic display and 3D visualization. He is the author and co-author of more than peer-reviewed articles and proceedings papers, as well as over 50 patents, abstracts and numerous invited lectures.

Liao was distinguished by receiving multiple government awards and various Best Paper Awards from different academic societies.

Furthermore, the rapid dissemination of smart devices bears the potential of automatic emergency alerts, which are transmitted between machines without any human in the loop. However, there is not yet any interconnection between the so far stand-alone information and communication technology ICT systems involved in accidents and emergencies, namely alerting systems e. Based on business analytics in the emergency care, we derive technological, syntactical, and semantical requirements for the ISAN.

We propose a compact alphanumeric representation that is generated easily but worldwide uniquely by the alerting system. Furthermore, an ISAN embeds time and position of the event and an identifier of the alerting system As an example, we show how the ISAN is used by a smart home to establish machine-to-machine communication. Also, ISAN is used to inform the smart home on arrival of the rescue team, and to transfer the fingerprint of the emergency physician such than she can open the door immediately.

Thomas M. Furthermore, Dr. This study focus on the development and application of robot techniques in spine surgery in our hospital.

It starts with an overview of the definition and development history of various robots, including the first medical robot which based on the industrial platform designed for stereotactic brain surgery.

The advantages and disadvantages of typical orthopaedic robots such as Acrobot precision surgical system, the RIO robotic arm interactive orthopaedic system and SpineAssist were also discussed. In robotic assisted spine technology, there were some technical difficulties related to safety issues, such as how to minimize the system error of the robotic system and how to present a virtual relevant anatomy to the doctors, and some difficulties related to surgical procedures, such as how to integrate these techniques into the already exist procedures.

For the questions which orthopaedic robots were facing, we shared our own experiences in design and current applications of orthopaedic robotic system.

In our strategies, we firstly improved navigation accuracy based on 3D images, then integrated the navigation system and robotic arm into a more complex orthopaedic robotic system. This orthopaedic robotic system was approved by CFDA with independent intellectual property rights.

This robot system includes a 6-degree of freedom DOF robotic arm and a real-time navigation system, the clinical error was smaller than 1. We have done multiple random study both on lumbar spine and cervical spine , which shows the accuracy of robot assisted spine pedicle implantation is much better than free hand method.

The application for the robot were not only limited in spinal surgery but also can be used in the traumatic surgery. Several cases assisted by this robotic system were shared. The challenges and research areas for the future progress in this field were also discussed.

Da He is an associate professor of spine surgery department, Beijing Jishuitan Hospital, the 4th clinical college of Peking University. Beijing Jishuitan Hospital is nationally renowned for its achievement and attainment in orthopaedics, and it ranks at 1st place for over 10 years in China, and spine surgery department is an acclaimed component of Jishuitan. Da HE receives over outpatients and completes cases of spine surgery every year. His research interests include navigation and robot assisted spine surgery, none fusion technology in spine.

At the hospitals, much of the workload consists of administrative and repetitive tasks. How about employing an administrative robot instead? Besides, they also have five backup robots that assist when called on, at any time during the hour. Our robotic co-Workers have reduced the time needed in these processes by thousands of hours per year. Created a faster flow of information, reduced waiting time for the patients, and increased the quality reduced the number of errors in the administrative systems, thereby improving the quality in the meeting between patient and care staff.

During the first years, it was a slow process to create robots due to the innovative way of using them. Considerations were taken to legislation questions as well as adapting to the existing IT-environment. Today the time needed to automate a process using RPA is a matter of weeks.

They were especially proven to be useful when the Covid pandemic increased pressure on the hospital and our staff. We could use our previous knowledge to quickly use more robots to help us out in the Pandemic situation. That saved meaningful time for staff that could better use this time for patient support. He has a Msc in mechanical engineering. His primary role as a development leader at the hospital is to assist in the overall development of the hospital and participate and achieve changes in specific areas or teams at the hospital.

He has both worked to create the existing solutions but also with the implementation of the robots in daily practice. This includes change management, day-to-day support, and present guidelines for working with a robot in your team. The orthopedic industry has an extremely broad market, with up to 20 million cases of bone trauma each year.

Surgery is the main treatment for most orthopedic diseases. However, due to the complex structure, deep location and rigid bone tissues, it is very difficult for surgeons to operate with bare hands, which brings an opportunity for the development of orthopedic surgical robot. China successfully performed its first orthopedic surgery with medical robot many years ago. With the support of national policies, a number of research institutes and hospitals have worked together to promote the development of orthopedic surgical robots in China.

At present, many orthopedic robot enterprises and products have been produced. In the future, orthopedic surgical robot will become more intelligent and personalized, so as to further improve the overall treatment in China. He participated in the development of the first domestic orthopedic surgical robot system of China, completed the first domestic robot-assisted orthopedic surgery and the first remote orthopedic surgery.

This achievement has successfully achieved industrial transformation. It is now the only domestic orthopedic surgical robot that has obtained CFDA product registration. He jointly applied for the Hong Kong Innovation Technology Fund project and developed the active and passive hybrid orthopedic surgical robot with the Chinese University of Hong Kong.

The system has been successfully applied in clinical practice and has been granted one US patent. He participated in the NIH RO1 project of the United States, and cooperated with Johns Hopkins University to carry out the research on hard tissue cutting technology based on continuum robot, and the related results were jointly published at the top international conference of robotics and biomedical Engineering.

Robots come in many different flavors. Apart from industry robots that have dedicated tasks without human interference, service robots are being developed that need to operate together with people. One example of such a robot is the social robot for independent living. As these social robots are becoming increasingly autonomous, they will require meaningful interaction capabilities to ensure efficiency and performance.

In this presentation, we will discuss three themes that are central for social robots for independent living. The first theme is navigation. When robots are applied in settings where they share a physical space with humans, they need to not only be able to navigate autonomously, but also do this in a socially acceptable manner.

They need to take personal space into account and understand other social conventions. The second theme is social cues. When navigating in an environment in which humans are present, robots need to be able to communicate where they are going to make their behavior predictable. While interacting with people, they also need to be able to communicate that they understand what the human wants and respond appropriately.

Robots can make use of social cues to achieve this. The third theme is social bonding. When having daily interactions with humans, robots need to be able to keep a record of their previous interactions, refer to them, and show that they remember what happened the previous day.

This makes people more likely to attribute emotions and a personality to the robot, gives them the feeling that they are understood, and allows them to create a social bond with the robot that is helping them to live independently at home for longer. With the recent advancements of medical robotic techniques, the alternative way to use conventional medical imaging systems could greatly improve the accessibility of the technique.

The design of such robotic systems are motivated by the challenges of manually holding and manipulating a probe: e. In this talk, the presenter, who is the main researcher of these systems, will share the story behind these robots and show the beautiful encounter of medical imaging and robotic intelligence. With a decreasing workforce of care professionals and to support an active and positive working life of informal carers, there is a need for assistive technologies at home such as social robotics.

The GUARDIAN project introduces a social companion, which aims to be of direct benefit for three groups of end-users; frail seniors, informal carers at work and formal carers.

A major challenge is that informal caregivers find it increasingly difficult to continue their work in addition to the care tasks they already have.

And when you also consider the increasing shortages in healthcare, the burden can become even higher. With Guardian, we therefore want to develop a robot companion with which the district nurse and informal caregiver can monitor his client, family or neighbour remotely. Vilans is the leading expertise centre on long-term care in The Netherlands. In the WP, a European Delphi study is performed in 6 countries and a systematic literature study. Henk Herman lead the research on the evaluation of the long-term care act in The Netherlands for the Ministry of Health.

At present, coronary artery disease CAD is the leading cause of death in the world. Many studies have proved that CAD may highly correlate with the motion of coronary arteries. Cardiovascular imaging technology is widely used for the diagnosis of CAD. However, it cannot directly calculate the motion parameters of the heart and coronary arteries.

Based on four-dimensional 4D coronary computed tomography CT images, we propose a point set registration method with global and local topology constraints to quantify coronary artery movement. The global constraint is motion coherence of the point set to enforce the smoothness of the displacement field. The local feature descriptor-3D shape context SC is exploited to capture the local positional information of the point set. Moreover, the local linear embedding LLE based topological structure is designed to retain the local spatial distance of the point set.

We embed these constraints into a maximum likelihood ML framework and derive the expectation-maximization EM algorithm to obtain the transformation function between the two point sets. The proposed method is compared with the current algorithms on the simulation data and tested in the real data, the experimental results demonstrate the effectiveness of the proposed approach for estimating the movement of coronary arteries.

Bu Xu is pursuing her Ph. Her current research interests include the areas of medical image analysis, computer vision, and pattern recognition. This paper proposed and evaluated an adaptive transfer function ATF based on multivariable regression to estimate the aortic pressure waveform from the brachial pressure waveform. Synchronous invasive aortic and brachial pulse waveforms were recorded from 34 subjects for the validation of the proposed method. Individual transfer functions ITFs from the raw and normalized brachial pressure waveforms were trained using an autoregressive exogenous ARX model.

Two generalized transfer functions GTFs were then derived: the first, by averaging the ITFs from the raw pressure waveform and the second, from its normalized counterpart.

The desired aortic pulse wave was reconstructed from the results of the two MATFs. The error of ED was The percentage errors of FF and AIx were It was concluded that the proposed method yielded better performance in estimating hemodynamic indices of aortic pressure waves than the GTF and ATF adjusted only by a single variable.

Shuo Du is a second year PhD candidate from college of medicine and biological information engineering, Northeastern University. Her current research interest is noninvasive estimation of central hemodynamic indices. Multi-viewpoints optical location system is an effective solution to the problems of light occlusion in optical positioning.

Moreover, it can reduce the blind areas in the operation and obtain a larger field of vision. In this study, multi-viewpoints optical positioning algorithm based on the optimal reconstruction accuracy is proposed to solve the problem of light occlusion in optical positioning. Firstly, a parallel multi-view camera array is established, and the unified coordinate system of multi-viewpoints is obtained through the camera calibration and coordinate transformation.

Then, according to the position relationship and the occlusion between the optical marker and each viewpoint, viewpoints are selected to reconstruct the coordinates of the optical positioning markers. Finally, the position of the positioning device is located according to the positional relationship between optical positioning markers and the tip of the surgical instrument.

The experimental results indicate that the proposed algorithm is able to accurately locate position of surgical instrument and track the surgical instrument in real-time when there exists light occlusion. His research interests include surgery navigation and medical image processing. Telemedicine can establish the relationship between clinical experts and patients to realize remote treatment and also can provide clinical teaching for medical students.

The combination of multi-viewpoint stitching and VR technology can expand the scope of surgical field and fully present realistic immersive surgical scene for telemedicine. Due to the complex operating room environment and the limited field of view, the surgical field cannot be completely obtained.

Moreover, there are many close-up objects with large deformation in the field of view. Thus, traditional feature based stitching algorithm is prone to stitching ghosting, object deformation and other artifacts. The Optical Positioning Algorithm with Motion Tracking OPAMT is adopted to obtain the strict one-to-one matching point pairs in high-attention area of the left and right views to overcome deficiency above. Then integrated with SIFT feature matching point pairs, more accurate local homography models are established.

Experiments on simulated surgery scenes demonstrate that the proposed algorithm achieves a better performance than the other state-of-the-art stitching algorithms. It can effectively improve the subjective quality of surgical panoramic stitching result.

In conclusion, it can expand the scope of surgical field and fully present realistic immersive surgical scene combined with VR for telemedicine. Her research current focuses on image stitching, point clouds registration. AI is promising to change healthcare. Care with AI is nonetheless problematic. Carefulness is key. Carelessness can be legally is costly. This presentation will explore some implications of AI in medicine, particular public liability issues, as well as changes to medical paradigm.

Finally, the concept of KIWI organizations is proposed and explained. This can frame and help better prepare hospitals and other organizations to harvest the benefits of digital health and AI in particular without neglecting the basics: knowledge, interoperability and wisdom. The project pursues an open innovation approach fostering uptake of digital health solutions making use of artificial intelligence, big data and internet of things technological paradigms involving ca He is author of more than 60 research work in internationally recognized journals and conferences, committee member of scientific conferences of biomedical engineering societies and associate editor of the IEEE Journal of Biomedical Informatics and Frontiers in Digital Health for the Connected Health section.

With the longest life expectancy in the globe and advanced medical conditions, population ageing bring grand challenges as well as opportunities for sustainable development. In order to organise an open, value-driven and trust-based arena, it is time to bring together older adults, their family caregivers, healthcare professionals, service providers, start-up entrepreneurs and the business sector to achieve optimal independency of older adults.

Methods: Aiming to garner and steer eHealth development, four user cases have been formed using risk stratification strategy. The four user cases including i a mobile app that serves as digital coach targeting ageing population with risk factors such as high-blood pressure, ii a sensor-based digital monitoring station targeting older adults living along, iii a community-based interoperable platform to analyse health characteristics and patterns of older adults via big data analytics, and iv a team-based mobile app targeting stroke families, comprising with stroke literacy education and personalised rehabilitation and social support planning.

Results: All the user cases were under development but impacted by COVID pandemic, we acknowledge the importance of following a combination of glocal management and agile development to ensure a smooth progress. As one of the Asian Pilots, we believe the user cases can set good references to local as well as global evidence-based eHealth research. Dr Lou Vivian W.

Dr Lou has studied widely on family caregiving, active aging, and their health impacts. Dr Lou also pioneered three mobile applications targeting volunteers, social workers, and stroke families respectively. She is now teaching social gerontology, clinical gerontology, and human development for both undergraduate and postgraduate students. Cybersecurity is in a critical state in the European Union and its member states. While the long-term negligence of the need to secure ICT is a global phenomenon, there are specific European challenges: Most major ICT providers are not headquartered in Europe, European research results are often not monetized in Europe and the Cybersecurity landscape is still fragmented.

Cybersec4Europe www. So CyberSec4Europe has the long-term goal of an EU able to secure and maintain a healthy democratic society, living according to European constitutional values wrt e. CyberSec4Europe is rooting its work in 7 application domains, whose needs will confront the state of research to achieve better solutions where possible and a strategic roadmap for what is missing. It is following the intentions of European legislation that reflects and protects European societal, democratic and economic norms and principles such as data protection and privacy.

CyberSec4Europe is organized as a research-based consortium working across four different but inter-related areas with a strong focus on openness and citizen-centricity in order to:.

This talk will introduce CyberSec4Europe and its major areas of work including the application oriented demonstrators. It will then especially introduce the demonstrator on medical data exchange. Before Kai had completed an Informatics-Diploma Master at TU Berlin with a focus on privacy, security, and distributed and real-time systems.

Kai has been coordinating several leading EU research projects, e. Today we are facing the global challenge of limited healthcare resources and unlimited needs. AI could be a silver bullet to address this challenge. AI can be applied from different angle to almost all healthcare areas to create value added solutions, for examples in BDA, AI technology has been used in rehabilitation, in surgery products, in manufacturing processes and in preclinical studies, etc.

In health as in many other sectors, the next major step in innovation is and will be driven by data and AI. AI holds the promise to radically change the way people work, the quality of work and life, it also is a needed driver to increase productivity growth to fuel our economies to be able to deal with the aging population. AI is not new, it exists for several decades, but major increases in data availability, network capacity and computing power have accelerated developments.

Not incremental but with a speed that was unimaginable even a few years ago. To focus on health, AI developments help efficiency, quality, and speed of all elements of a patient journey, from first complaints to treatment and revalidation, while significantly reducing costs and improving patient care and experience.

Policy must set the boundaries, but technology must find the solutions. A case for cardiovascular disease will exemplify how different approaches can be developed to comply with ethical standards and at the same time optimize a networked and distributed system. Robbert is an innovation policy and strategy expert, currently focusing on AI in distributed environments in health.

He has led and worked on large assignments for the European Commission, the European Parliament, the EIB, national governments and private firms. Robbert has founded two start ups, of which one was a very early days big data analytics company.

Rehabilitation medicine is an important part of modern medicine. Public demand for rehabilitation has been an explosion in China not only because the growth rehabilitation needs of outpatients and discharged patients, but also because the accelerating population ageing further boosts the demand.

Nevertheless, current system of rehabilitation in China is facing some problems, including the shortage and uneven distribution of medical resource, lack of standards, difficulty of inter-agency information sharing and lag in equipment and facilities. The first one is the regional network pattern which is usually initiated by a regional government to establish a network of rehabilitation services including 3-tier medical institutions in its administrative area.

The second one is the hospital-centered pattern which refers to a network of rehabilitation services with a large official general hospital as its core, and some other rehabilitation institutions of lower levels as the subordinate institutions.

And lastly, just as its name implies, the third-party Internet platform pattern means that a third-party company offers its Internet platform to integrate rehabilitation service resources from different places and to efficiently match targeted services to patients who make their appointments in advance. Each pattern already has its mature cases after years of exploration and development in China.

Yuan Changrong, Ph. D, Ph. Yuan held more than 20 funded research projects related to cancer nursing, nursing informatics and long-term care, including National Natural Science Foundation of China, Foundation of American Oncology Nursing Society and International Science and Technology Cooperation Program.

More than 40 Master, Ph. D and post-doctoral students had been successfully graduated with the guidance of Prof. In and , she was selected as a High-citation Scholar in China published by Elsevier. Gatekeeper was born from the necessity of providing a full standard and certified approach for data governance in healthcare, designed for the enhancement of data economy, providing solutions for data interoperability and re-use in machine learning ML and artificial intelligence AI algorithms ensuring data quality, protection, privacy and security.

Furthermore, along with web technologies such as REST-API and Web Socket , blockchain containerization and orchestration technologies suck as Docker and Kubernetes are used to build a resilient, scalable, secure and certified digital platform designed for data governance in the healthcare domain.

At the current state within the Gatekeeper project there has been already defined a first release of the Gatekeeper digital platform, and a standard and common data space based on FHIR standard that will be populated by 8 pilot sites in Europe and 3 pilot sites in Asia. Furthermore, within the pilots, Gatekeeper aims to create an artificial intelligence ecosystem based on the concept of the Gatekeeper data space that will contribute to the HealthCare Data Space foreseen at European level, with the objective of providing services for early prevention and intervention in 7 Medical Reference Use Cases RUCs in order to improve the accessibility, effectiveness and sustainability of the healthcare systems.

The aim of Gatekeeper project is to enhance collaboration worldwide, by promoting a collaborative environment based on fully standard, interoperable and open source solutions. His expertise is in wireless networks, wearable sensor, physical activity monitoring, machine learning and artificial intelligence, mobile Health platforms and Apps development.

He was founder and CTO of Maketag s. Maketag was acquired by BuzzMyVideos l. Furthermore, he is involved in the Horizon project Plan4Act H that is a FET project that will record and understand predictive neural activity in no human primate and use it to proactively control devices in a smart house. Background: Big Data Technologies have been applied in Healthcare sector providing significant advantages on both the quality of the healthcare services and the control of the cost. Specific Big Data analytic techniques can lead to effective fraud detection in the health domain.

What we did? To analyze the data for fraud detection, prescription data of the following product categories were extracted: i Products and Supplies for Diabetes Management, ii Catheters, iii Medical Pads, and iv Special Nutrition Products and Supplements. The aforementioned raw data were transformed in a manner to describe new features for each product based on the number of the cases. Specifically, the following features were calculated: i the number of the prescriptions, ii the number of patients who received each product, iii the number of prescribers who prescribe each product, iv the number of prescription to the number of patients ratio, v the number of prescription to the number of prescribers ratio, vi the number of the maximum prescriptions per patient, and vii the number of the maximum prescriptions per prescriber.

Athens University of Economics and Business. Audiovisual Technologies, Informatics and Telecommunications bvba. Augsburg University of Applied Sciences. Australian Academy of Technological Sciences and Engineering. Australian Institute of Company Directors. Austrian Academy of Sciences, Austria". Austrian Assocciation for Agricultural Research. Austrian Institute of Technology, Seibersdorf.

Autorita per l'Energia Elettrica il Gas e il sistema idrico. Banca Monte dei Paschi di Siena S. BarcelonaBeta Brain Research Centre.

Pasqual Maragall Foundation. Basque Center on Cognition, Brain and Language. Basque Foundation for Health Innovation and Research. Bavarian Agency for Surveying and Geoinformarion. Beckman Research Institute of the City of Hope. Beijing University of Chemical Technology. Belgian User Support and Control Centre. Bellos Vasileios Sole Proprietorship. Bellvitge Biomedical Research Institute.

Bernstein Network Computational Neuroscience. Biberach University of Applied Science. Biocant Park - Association for Technology Transfer.

Biogazownie Polskie Sp. Biomedical Research Center "Alexander Fleming". Biomedical Research Foundation Academy Athens. Biomedical Research Foundation Academy of Athens. Biomedical Research Foundation of Athens Academy. Biomedical Research Foundation of the Academy of Athens.

Biomedical Research Foundation, Academy of Athens. Biomedical Sciences Research Center 'Al. Biosckin, Molecular and Cell therapies SA. Biotechnical Faculty, University of Ljubljana. Birkbeck College University of London. Black Sea Agricultural Research Institute. Black country partnership nhs foundation trust. Bogazici University, Institute of Biomedical Engineering. Bombardier Transportation Austria GmbH. Borderstep Institute for Innovation and Sustainability.

Bradford University School of Management. Budapest Institute for Policy Analysis. Budapest University of Technology and Economics. Bulgarian Chamber of Mining and Geology. Bulgarian Defence Institute "Prof. Tsvetan Lazarov". Bulgarian Environmental Partnership Foundation. Bulgarian Industrial Capital Associations. Bundesverband IT-Mittelstand e. Bundesverband Interaktive Unterhaltungsoftware e. Bureau for Mechanical and Energy Engineering. Business and Innovation Agency Croatia.

Buskerud and Vestfold University College Norway. Smetonos g. California Polytechnic State University. California State University International Program. Camara Nacional de Turismo de Honduras. Cambridge Architectural Research Limited.

Cambridge Nanomatrials Technology Ltd. Cambridge University Science Policy Exchange. Capricorn Venture Partners previously Quest Management. Capsicum Management und Beratungs GmbH. Cardinal Stefan Wyszynski University in Warsaw.

Carinthian University of Applied Sciences. Carl von Ossietzky University Oldenburg. Catalonia Institute for Energy Research. Catalonia Science and Innovation Foundation. Catholic University Leuven, faculty of Medicine,. Catholic University of the Sacred Heart. Catholic University of the sacred heart. Perutz Laboratories. Center for Neuroscience and Cell Biology.

Center for Physical Sciences and Technology. Center for Transportation Studies, Boston U. Center for translational molecular management. Centers for Disease Control and Prevention. Central European Institute of Technology. Central Institute for Meteorology and Geodynamics. Central Laboratory of Footwear Industry. Central Research Institute for Field Crops. Centre Hospitalier Universiataire and University of Picardie. Centre Hospitalier Universitaire Vaudois. Centre National d'Etudes Spatiale, Paris.

Centre National d'Etudes Spatiales. Centre National de La Recherche Scientifique. Centre National de Recherche Scientifique. Centre National de la Recherche Scientifique. Centre National pour La recherche Scientifique. Centre National pour la Recherche Scientifique. Centre Tecnologic de Telecomunicacions de Catalunya.

Centre d'excellence en Technologies de l'Information et de la Communication. Centre de Physique de Particules de Marseille. Centre de Recherche Public Henri Tudor.

Centre for Advanced Study Sofia Foundation. Centre for Applied Bioethics, University of Nottingham. Centre for Diaspora and Transnational studies, University of Toronto. Centre for Economic Development, Transport and the Environment. Centre for Evolution, Genomics and Bioinformatics. Centre for Mobility and Educational and Training Programmes. Centre for Process Innovation Limited. Centre for Research and Technology Hellas. Centre for Studies in Social Sciences, Calcutta.

Centre national de la recherche scientifique. Centre national de la recherche scientifique - INCI. Centre of Excellence in Nanoscience and Nanotechnology.

Centre of Water Research and Technologies. Centro Hospitalar Universitario de Coimbra. Centro Nacional de Investigaciones Cardiovasculares. Centro Nacional de Investigaciones Oncologicas.

University of Santiago de Compostela. Chalmers University of Technology, Sweden. Chancellery of the Parliament of the Republic of Lithuania. Charles University - 2nd Medical Faculty. Charles University, 1st Medical Faculty. Charles University, Faculty of Natural Sciences. China Europe International Business School. Chinese Academy of Geological Sciences. Christian-Albrechts-University of Kiel. Cities on the Move Asociatia Orase in Miscare.

Civitta International previous Advisio Ltd. Clarendon Laboratory, University of Oxford. Clinic of Endocrinology, Diabetes and Disease of Metabolism.

Cluster "Innovation and ecology technologies green building and RES". Cluster of Transport and Logistics of the Canary Islands. Coimbra Superior Institute of Engineering.

Cologne University of Applied Sciences. Columbia University, Department of Mathematics. Comenius University School of Medicine. Commissariat a l'Energie Atomique. Condensed Matter Physics Department". Confederation of Family Organisations in the EU. Conflict Conflict Resolution Training and Consultancy. Consejo Superior de Investigaciones Cientificas.

Conservation Consultants Sara van Rompaey. Conservatoire National des Arts et Metiers. Consiglio per la Ricerca e Sperimentazione in Agricoltura. Consiglio per la ricerca e la sperimentazione in agricoltura. Consultores de Automatizacion y Robotica S. Copenhagen University Hospital Hvidovre. Creative Industry Cluster of South Transdanubia. Croatian Association of Drink Producers. Croatian Financial Services Supervisory Agency.

Croatian Pension Investment Company Ltd. Croatian veterinary Institute, Poultry Centre. Customs department under the Ministry of Finance. Cyprus Neuroscience and Technology Institute. Daithi O'Murchu Research Station,. Danish Health and Medicines Authority. Danish Institute for International Studies. Danish and Greenlandic Geological Survey.

Danube University Krems - Business School. Decentralized Administration of Macedonia and Thrace. Dee Associates Business Consultants Limited. Democritus University of Thrace Medical School. Departamento de Engenharia Electrotecnica. Department for Food and Rural Affairs. Department of Analytical and Environmental Chemistry". Department of Biological Sciences, University of Lincoln. Department of Chemistry and Bioscience". Department of Chemistry, K. Department of English and Comparative Literature".

Department of Geography, University of Cambridge. Department of Mathematics and Applications. Department of Pharmacology and Pharmacotherapy, Semmelweis University. Department of Pharmacy and Pharmacology, University of Bath. Department of Philosophy, University of Massachusetts. Department of Physics - Aristotle University of Thessaloniki. Department of Physics and Astronomy, University of Sheffield. Department of Political Science, Lund University. Department of Political Science, University of Geneva.

Department of Sociology, University of Copenhagen. Dept Agriculture, Food and the Marine. Dept of Chemistry, University of North Texas. Deutsche Forschungsgemeinschaft DFG. Digital Archiving Consultancy Limited. Dipartimento Scienze Geologiche Roma Tre. Direction Generale de Finance Publiques. Discover, Exchange, Consulting, Conference, and Seminars. Dokuz Eylul University Medical Faculty. Dokuz Eylul University Medical School. Donders Institute for Cognitive Neuroscience. Ursula Pretterhofer, Unternehmensberatung.

Weichert - Life Sciences Consulting. Drilling and Geological Works Company Ltd. Duanrea de Jos university of Galati Romania. Dublin Institute for Advanced Studies. Dublin Institute of Technology, School of Physics.

Duke University, Department of Physics. Dundee City Council and partner councils. Dutch Institute for Advanced Logistics. Dutch Ministry of Infrastructure and Environment. Andalusian Regional Health Emergency System. EU programmes and projects Consult Ltd.

Earthy Matters Environmental Consultants. Eberhard Karls University of Tuebingen. Ecole Polytechnique Federal de Lausanne. Ecole Polytechnique Federale Lausanne. Ecole Polytechnique Federale de Lausanne.

Ecole des Hautes Etudes en Sciences Sociales. Educational and Cultural Ladin Department. Ege University, Faculty of Agriculture. Electronic Commerce Competence Centre. Electronic Government and Inf. Society Agency. Elsevier - Renewable and Sustainable Energy Reviews.

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