Second edition of the Symposium "AI and Medicine: Promises and Limits"

Given the success of its first edition, MIT, the Académie Nationale de Médecine and the Health Data Hub organized the "AI and Medicine" Symposium again. It took place on October 20, 2022 at the Académie Nationale de Médecine in Paris in the presence of American and European experts who discussed the connection between AI and medicine.  

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The MIT Computer Science and Artificial Intelligence Lab (CSAIL), the MIT Institute for Medical Engineering and Science (IMES), the Académie Nationale de Médecine and the Health Data Hub once again joined forces to organise the second edition of the symposium "Artificial Intelligence (AI) and Medicine: Promises and Limits". The Symposium was held this year at the Académie Nationale de Médecine in Paris, on the afternoon of October 20th. For this new edition, the panel of speakers, both American and European, was composed of experts from the organisations part of the organising committee as well as representatives from major American and European research institutes and universities, but also of representatives of the national authorities in charge of AI and health.  For the first time this year, the organising committee was pleased to associate the French Embassy in the United States to this event. 


The Symposium was structured around three conferences during which experts, researchers, entrepreneurs and decision-makers will exchange views. Following on from the first edition, the aim of these discussions was to shed light on the approaches taken in AI and health on both sides of the Atlantic and to exchange views on the possibilities and practical realities of these approaches. 


The main themes selected for this second edition and the questions it attempted to answer are those of access to health data at national and international level, the challenges of AI in medicine and the ways in which medicine can benefit from AI. The resulting discussions  addressed a variety of issues, including context and challenges on both sides of the Atlantic, algorithm validation and potential AI biases, clinician needs and human-computer interaction. 


Please find below the programme of the event as well as the replay of the first edition.

14:00 - Welcome address by Patrice Tran Ba Huy, President of the Académie Nationale de Médecine


14:10 - Opening

  • Bernard NordlingerPresident of the Committee for Digital Medicine, Académie Nationale de Médecine
  • Daniela Rus, Director of the CSAIL, MIT, Deputy Dean of Research at the Schwarzman College of Computing, MIT


14:15 - Session 1 : Access to health data at a national and international level

This session will address the challenges of using shared data as well as the issues of data protection, interoperability and data federation. The discussions will involve a comparison of the situation and challenges in Europe and in the US.

  • Emmanuel Bacry (moderator), Chief Scientific Officer of the Health Data Hub
  • Leo Anthony CeliPrincipal Research Scientist at MIT, Associate Professor of Harvard Medical School, Instructor at Harvard T.H. Chan School of Public Health
  • Hervé DelingetteResearch Director Inria & 3IA Côte d'Azur
  • Andrzej RysDirector for Health Systems and Products at the European Commission
  • Irene Schluender, Lawyer, BBMRI 


15:30 - Session 2 : Challenges for AI in medicine

This session will address the creation of training and testing sets with health data as well as reflect on what constitutes the gold standard for AI in medicine. It will also tackle the issues of validating AI algorithms and certifying AI embarked devices and of the potential biases.

  • Daniela Rus (moderator), MIT, CSAIL
  • Corinne CollignonHead of Department, Digital Health Mission, Haute Autorité de Santé
  • Michel DumontierDistinguished Professor of Data Science at Maastricht University
  • Marc JulienCo-CEO and COO at Diabeloop
  • Nancy Miller Rich, Nancy Miller Rich, Chairman of Biotheryx, a director at Intercept Pharma, Alderyra Pharma, Attralus Therapeutics, 4DMT and a founder and advisor to Ten63
  • Farhad Rikhtegar NezamiLead Investigator, Brigham and Women’s Hospital, Faculty Member, Department of Surgery, Harvard Medical School


17:00 - Break


17:30 - Session 3 : How can medicine benefit from AI?

This session will address three different topics beginning with drug development, followed by the needs of clinicians in clinical trials and lastly the human computer interaction.

  • Elazer R. Edelman (moderator), Director of the IMES, MIT, Edward J. Poitras Professor in Medical Engineering and Science at MIT, Professor of Medicine at Harvard Medical School
  • Bernard Nordlinger (moderator), President of the Committee for Digital Medicine, Académie Nationale de Médecine

PANEL 1 : Drug discovery

  • Leo Anthony CeliMIT, Harvard Medical School, T.H. Chan School of Public Health
  • Nicolas Do HuuCo-founder and Chief AI Officer at Iktos
  • Farhad Rikhtegar Nezami, Brigham and Women’s Hospital, Harvard Medical School

PANEL 2 : Clinical trials, what clinicians need

  • Stéphanie AllassonnièreProfessor and Vice-President Valorisation at University Paris Cité, Chaire PR[AI]RIE at Institut PR[AI]RIE, Associate Professor at Ecole Polytechnique
  • Jean-Yves BlayHead of Department of the Léon Bérard Center, President of UNICANCER
  • Ozanan MeirelesDirector of the Surgical Artificial Intelligence and Innovation Laboratory at Massachusetts General Hospital, Assistant Professor of Surgery at Massachusetts General Hospital and Harvard Medical School
  • Leo Anthony Celi, MIT, Harvard Medical School, T.H. Chan School of Public Health

PANEL 3 : Human computer interaction

  • Bernard BioulacProfessor emeritus at the University of Bordeaux, Former Deputy Chief Scientific Officer in charge of neurosciences at the Institute of Biological Sciences of the CNRS, member of the National Academy of Medicine
  • Blaise YvertInserm Research Director at Institute of Neuroscience of Grenoble
  • Ozanan Meireles, Massachusetts General Hospital, Harvard Medical School


19:15 - Summation


19:30 - Cocktail