MD, PhD. Professor of Medical Informatics at Université de Paris. Chair of the Department of Medical Informatics at Georges Pompidou and Necker Hospitals (AP-HP). Leader of the «Information science to support personalized medicine» research group at Cordeliers Research Center.
Topics of interest
Medical decision, Electronic Health Records, Natural Language Understanding
Project in Prairie
Anita Burgun’s objectives are to develop AI systems that can be used to support medical decision in clinics, like hybrid approaches combining learning algorithms and logics. Examples are deep phenotyping based on the EHR, similarity metrics in rare diseases, and precision medicine. She will participate in AI programs for undergraduate and graduate medical students, as well as AI in medicine summer school.
The development of Artificial Intelligence for clinical decision cannot be achieved without hybrid approaches, to learn from a limited number of heterogeneous cases, with complex phenotypes, and complex underlying biological mechanisms. Solutions based on deep phenotyping are being investigated to solve a diagnostic or a therapeutic problem of a new patient by recalling previous cases that exhibited similar characteristics in rare disease clinical data warehouses. Future directions consist in developing digital twins solutions that integrate the precision medicine paradigm. Such approaches combine different methodologies, using holistic omics data, and existing data from clinical trials and routine care. Because of data complexity, multi-scale knowledge, and fast changing models, AI in medicine raises lots of issues that require multidisciplinary research at the highest level.