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Doctors in Medical Data Sciences: A New Curriculum

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 prac...

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Detalles Bibliográficos
Autores principales: Cussat-Blanc, Sylvain, Castets-Renard, Céline, Monsarrat, Paul
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9819870/
https://www.ncbi.nlm.nih.gov/pubmed/36612994
http://dx.doi.org/10.3390/ijerph20010675
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author Cussat-Blanc, Sylvain
Castets-Renard, Céline
Monsarrat, Paul
author_facet Cussat-Blanc, Sylvain
Castets-Renard, Céline
Monsarrat, Paul
author_sort Cussat-Blanc, Sylvain
collection PubMed
description 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.
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spelling pubmed-98198702023-01-07 Doctors in Medical Data Sciences: A New Curriculum Cussat-Blanc, Sylvain Castets-Renard, Céline Monsarrat, Paul Int J Environ Res Public Health Viewpoint 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. MDPI 2022-12-30 /pmc/articles/PMC9819870/ /pubmed/36612994 http://dx.doi.org/10.3390/ijerph20010675 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Viewpoint
Cussat-Blanc, Sylvain
Castets-Renard, Céline
Monsarrat, Paul
Doctors in Medical Data Sciences: A New Curriculum
title Doctors in Medical Data Sciences: A New Curriculum
title_full Doctors in Medical Data Sciences: A New Curriculum
title_fullStr Doctors in Medical Data Sciences: A New Curriculum
title_full_unstemmed Doctors in Medical Data Sciences: A New Curriculum
title_short Doctors in Medical Data Sciences: A New Curriculum
title_sort doctors in medical data sciences: a new curriculum
topic Viewpoint
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9819870/
https://www.ncbi.nlm.nih.gov/pubmed/36612994
http://dx.doi.org/10.3390/ijerph20010675
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