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Doctors in Medical Data Sciences: A New Curriculum

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  • Sylvain Cussat-Blanc

    (Artificial and Natural Intelligence Toulouse Institute ANITI, 31013 Toulouse, France
    Institute of Research in Informatics (IRIT) of Toulouse, CNRS—UMR5505, 31400 Toulouse, France)

  • Céline Castets-Renard

    (Artificial and Natural Intelligence Toulouse Institute ANITI, 31013 Toulouse, France
    Civil Law Faculty, University of Ottawa, Ottawa, ON K1N 6N5, Canada)

  • Paul Monsarrat

    (Artificial and Natural Intelligence Toulouse Institute ANITI, 31013 Toulouse, France
    RESTORE Research Center, Université de Toulouse, INSERM, CNRS, EFS, ENVT, Batiment INCERE, 4bis Avenue Hubert Curien, 31100 Toulouse, France
    Department of Oral Medicine, Toulouse University Hospital (CHU de Toulouse), CEDEX 9, 31062 Toulouse, France)

Abstract

Machine Learning (ML), a branch of Artificial Intelligence, which is competing with human experts in many specialized biomedical fields and will play an increasing role in precision medicine. As with any other technological advances in medicine, the keys to understanding must be integrated into practitioner training. To respond to this challenge, this viewpoint discusses some necessary changes in the health studies curriculum that could help practitioners to interpret decisions the made by a machine and question them in relation to the patient’s medical context. The complexity of technology and the inherent criticality of its use in medicine also necessitate a new medical profession. To achieve this objective, this viewpoint will propose new medical practitioners with skills in both medicine and data science: the Doctor in Medical Data Sciences.

Suggested Citation

  • Sylvain Cussat-Blanc & Céline Castets-Renard & Paul Monsarrat, 2022. "Doctors in Medical Data Sciences: A New Curriculum," IJERPH, MDPI, vol. 20(1), pages 1-5, December.
    • Handle: RePEc:gam:jijerp:v:20:y:2022:i:1:p:675-:d:1020218
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