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个人简介
I followed a double curriculum in medicine & science at University of Paris driven by my curiosity for cognition and neuroscience. I did my master 2 in Cognitive neuroscience at ENS and several medical internships in neurology and psychiatry.
I finally opted for a specialization in public health, because my interest evolved more towards the understanding and abstraction of learning principles, and their implementation in machines. Indeed, public health addresses medical questions at the population level, and I thought that machine learning would naturally be useful.
During my public health residency, I conducted collaborative research projects in medical informatics (2 NLP publications: classifying clinical trials abstracts to be included in reviews, extracting clinical entities from medical records), biostatistics (oral presentation at ISCB: simulation study showing links between non-proportional hazards and composite endpoints in Cox regression) and epidemiology (under submission: prognosis value of troponin in population).
To make sense of such diverse experiences, a unifying theoretical framework was needed, which I found in the theory of causality while attending a lecture by Peters.
I have now started a part-time PhD on Machine Learning for Health (supervisors Francis Bach and Anita Burgun), where I am working on developing structure learning algorithms for electronic medical record data, which I believe is essential to achieve robust transfer learning.
At the same time, I hold a position as a university hospital assistant at the Department of Medical Informatics of the Hôpital Européen Georges Pompidou, where I bring my expertise to local research projects, and I teach medical students at the University of Paris.
Being part of the INSERM-INRIA HeKA team (https://team.inria.fr/heka/fr/), my research work is part of a larger effort by the team to bridge the gap between care and research by developing methodological and technical tools for the use of real life data in a "learning health system". Within this framework, we aim to create a cycle between modeling based on real life and experimental data, and the deployment of these models to support clinical decision making
研究兴趣
论文共 27 篇作者统计合作学者相似作者
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Antoine Neuraz,Ivan Lerner, Olivier Birot,Camila Arias,Larry Han,Clara Lea Bonzel,Tianxi Cai, Kim Tam Huynh,Adrien Coulet
Studies in health technology and informatics (2024): 649-653
J. Slomka,H. Berthou, A. Lupo-Mansuet,H. Blons,E. Fabre,I. Lerner,B. Rance, G. Birsen,J. Chapron,L. Gibault,J. Arrondeau,K. Leroy,
Revue des Maladies Respiratoires Actualitésno. 1 (2023): 142
Jean-Philippe Empana,Ivan Lerner,Eugenie Valentin,Fredrik Folke,Bernd Böttiger,Gunnar Gislason,Martin Jonsson,Mattias Ringh,Frankie Beganton, Wulfran Bougouin,Eloi Marijon,Marieke Blom,
Jean‐Philippe Empana,Ivan Lerner,Eugénie Valentin,Fredrik Folke, Böttiger,Gunnar Gislason,Martin Jönsson,Mattias Ringh,Frankie Beganton, Wulfran Bougouin, Éloi Marijon,Marieke T. Blom,
Zenodo (CERN European Organization for Nuclear Research) (2022)
J P Empana,I Lerner,M C Perier,P Jabre,M Andrieu,R E Climie,T Van Sloten, B Vedie, D Geromin,E Marijon,N Danchin, F Thomas,
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