PhD, FACMI, FIAHSI
Professor of Practice of Computing Science, School of Computing, National University of Singapore
Director of AI Technology, AI Singapore
Tze-Yun LEONG is Professor of Practice of Computer Science at the School of Computing, National University of Singapore. She is also Director of AI Technology at AI Singapore, a national program on Artificial Intelligence. She is an elected Fellow of the American College of Medical Informatics (ACMI) and a founding Fellow of the International Academy of Health Sciences Informatics (IAHSI).
Tze-Yun received her SB, SM, and PhD degrees in Electrical Engineering and Computer Science from the Massachusetts Institute of Technology (MIT), USA. Her research interests include decision-theoretic artificial intelligence, cognitive modelling, machine learning, adaptive computing and biomedical and health informatics. She has over 150 international peer-reviewed publications. She has also served on editorial boards and program committees of leading international journals and conferences on artificial intelligence and biomedical informatics.
With both academic background and business experience, Tze-Yun regularly contributes to panels and committees that advise on R&D directions and education in computer science, artificial intelligence and health informatics in Singapore and abroad. She served as Working Committee Member of the Information and Communication Technology and Media Master Plan 2025 in Singapore (2013-2015), Advisory Board Member of the United Nations University Institute for Computing and Society (UNU-CS) (2012-2016), and Vice President overseeing the working groups and special interest groups of the International Medical Informatics Association (IMIA) (2013-2016).
Vivian Beaumont Allen Professor and Chair of Biomedical Informatics
Columbia University, New York, NY
Director of Medical Informatics Services
New York-Presbyterian Hospital/Columbia Campus, New York, NY
George Hripcsak, MD, MS, is Vivian Beaumont Allen Professor and Chair of Columbia University’s Department of Biomedical Informatics and Director of Medical Informatics Services for New York-Presbyterian Hospital/Columbia Campus. He is a board-certified internist with degrees in chemistry, medicine, and biostatistics. Dr. Hripcsak’s research focus is on the clinical information stored in electronic health records and on the development of next-generation health record systems. Using nonlinear time series analysis, machine learning, knowledge engineering, and natural language processing, he is developing the methods necessary to support clinical research and patient safety.
He leads the Observational Health Data Sciences and Informatics (OHDSI) coordinating center; OHDSI is an international network with 200 researchers.
Dr. Hripcsak is a member of the National Academy of Medicine, the American College of Medical Informatics, the International Academy of Health Sciences Informatics, and the New York Academy of Medicine. He has published over 350 papers.
Pr. Jacques Demongeot,
Emeritus at University Grenoble Alpes, Faculty of Medicine, Laboratory AGEIS
Professor Jacques Demongeot obtained his academic degrees at Grenoble University J. Fourier (now University Grenoble Alpes, UGA): PhD & MD Thesis, Dr. ès Sciences Mathématiques, Agrégation de médecine (Medicine Professorship).
He is presently Emeritus at UGA, Honorary Member at Institut Universitaire de France (IUF) and Foreign Member of the Chilean Academy of Sciences.
He has been appointed to various academic positions: Director of the Laboratories CNRS TIM3 and TIMC-IMAG between 1987 and 2011, Director of the Doctoral School EDISCE (1996-2007), Head of the Missions «Technology for Health» and «Systems Biology & Complexity» at the Ministry of Research and at CNRS (1997-2006). He has been Project Leader of different European projects: Biomed ISCAMI (Integrated System for Computer Aided Medical Interventions), BMH MDMO (Matching of Deformable Medical Objects) and ALFA (America Latina Formacion Academica) IPECA.
He pioneered in different fields like biological modelling (neural and genetic Boolean networks), dynamical systems (attractors theory), image processing, medical informatics (Cristal-Net®, hospital information system), epidemiology and e-health. He is the author of about 400 scientific papers and 16 world patents.
From biological genotype to digital phenotype
Phenotype is related to the observable morphology and behavior of a living system and genotype refers to the information stored in classes of systems, which partly conditions the phenotype, the latter resulting from an interaction between genotype and environment. These notions of phenotype and genotype, common in biology, have currently an equivalent in social sciences, where one can speak i) of a digital phenotype, which refers to the behavior of individuals using digital devices (computer, tablet, telephone, connected objects, ...) and ii) of a digital genotype, constituted from databases storing an information common or specific to these individuals.
The digital phenotype can be observed through the behaviors of use of connected objects recorded through a statistical monitoring of the telephone traffic (like that carried out by a telephone provider like Orange®) observed through networks of social services, or from individual surveillance of elderly people at home, particularly in the context of smart apartments.
The digital genotype comes from the classification of individuals highly connected in social networks, sharing the same rules of socio-cultural life. The traits characterizing these groups are called "social genes" because they transcend generations, are in part inherited and can be composed of "atoms" of knowledge (from family and social habits, common rules about food, sports and cultural activities, as well as reference behaviors learned at the same educational level).
We will give examples of practical use of the two notions of digital phenotype and genotype in surveillance of chronic diseases like neurodegenerative disorders and obesity.
T. AUBOURG, F. RENARD, H. PROVOST, J. DEMONGEOT & N. VUILLERME
Estimates of digital circadian rhythms in older adults: a comparison between data collected from outgoing and incoming phone calls
JMIR mHealth & uHealth (accepted).
Binyam Tilahun, PhD, MSc, MPH
eHealthLab Ethiopia leader
Assistant Professor, Health Informatics & Implementation Sciences
Chief Director for Research, Technology Transfer, and Community Services
University of Gondar
Binyam Tilahun is currently leader of eHealthLab Ethiopia, Assistant Professor of Health Informatics & Implementation Sciences and Chief Director of Research, Technology Transfer, and Community Services at the University of Gondar. In his research group, he leads different global health informatics projects in the areas of eHealth, mHealth and Big Health Data and data use with funding from major national and international organizations including: World Health Organization(WHO), Bill & Melinda Gates Foundation (BMGF), European Union, Ethiopian Ministry of Health, Doris Duke Charitable Foundation, Grand Challenges Ethiopia.
Binyam Tilahun completed his Postdoctoral fellowship from the University of the British Columbia in Canada, received his PhD in Medical Informatics from the University of Münster, Germany and a master’s degree in Public Health with Health Informatics specialization from the University of Gondar. On his return to his country, he leads the development of the first PhD level programs in Health informatics in Africa and the first bachelors level program in health informatics where more than 200 students graduated who are currently working at the different levels of the health system of Ethiopia. At present, Dr. Tilahun is working with other universities to expand health informatics education to other five Universities with the vision of training 2,000 bachelors level, 80 masters level, and 10 PhD level health informatics professionals in the coming five years. He is currently closely working with FMOH in Capacity Building and Mentorship Partnership (CBMP) and Data Use Partnership (DUP) projects focusing on National Level Capacity building, Embedded Implementation science research and technical assistance for regions, districts and facilities to have sustainable health information systems in the country.
Directeur Général EIT Health France
Investment committee member TTO Lutech
EIF – EIT Health European Venture Center of Excellence Leader
After studying medicine in Lille and marketing in a business school in Paris, Jean Marc Bourez has experienced different positions in pharma industry since 1992, Commercial Operations, Medical Affairs, Strategic Marketing, Business Excellence, Business Development Strategy and Open Innovation. Former head of eHealth & Open Innovation process at Sanofi, he has been appointed as CEO of EIT Health France, a Knowledge Innovation Community supported by European Institute of Technology, a body of the European Union. In this position, Jean-marc is leading a collaborative project with the European Investment Fund to develop a pan-European Platform of co-investment in Life sciences. Jean-Marc is also Chairman and co-founder of a MedTech Company founded in 2017.
The European perspective
The European Union is currently working to encourage more effective use of information and communications technology, in particular for delivery of health services, including disease prevention and health promotion, and has various initiatives and strategies in place. The European Commission has allocated €2 billions under the Horizon 2020 program for research and innovation in Big Data under the call ‘Personalising Health and Care’ and has since April 2018 a supportive policy for digital transformation of health and care with a strong focus on Big Data.
The role of EIT Health
In recognition of the considerable challenges across Europe but also the immense opportunities in this sector, ‘The use of existing Big Data to improve healthcare’ was selected as a topic for the EIT Health Think Tank for 2018. The task was to evaluate the current position in Europe, identify barriers, recommend strategies to overcome them, and propose actionable projects and activities to make the best use of Big Data at a regional and European level for the benefit of citizens. 3 axes have been prioritized to develop concrete achievements: 1. Identifying and harnessing the benefits of available data, 2. Building capacities/capabilities to realize benefits, 3. Community engagement and participation