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pro vyhledávání: '"Elodie, Escriva"'
Decision support tools in healthcare require a strong confidence in the developed Machine Learning (ML) models both in terms of performances and in their ability to provide users a deeper understanding of the underlying situation. This study presents
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3ef879f934e47b29f1bec12d682435e5
https://doi.org/10.3233/shti220520
https://doi.org/10.3233/shti220520
Publikováno v:
Studies in health technology and informatics. 294
Decision support tools in healthcare require a strong confidence in the developed Machine Learning (ML) models both in terms of performances and in their ability to provide users a deeper understanding of the underlying situation. This study presents
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmid________::7a553d83ba1b5e2e5f6175e753053b06
https://pubmed.ncbi.nlm.nih.gov/35612141
https://pubmed.ncbi.nlm.nih.gov/35612141
Autor:
Gabriel Ferrettini, Chantal Soulé-Dupuy, Julien Aligon, Jean-Baptiste Excoffier, Elodie Escriva
Publikováno v:
Information Systems Frontiers
Information Systems Frontiers, Springer Verlag, 2021, pp.1-31. ⟨10.1007/s10796-021-10141-9⟩
Information Systems Frontiers, Springer Verlag, 2021, pp.1-31. ⟨10.1007/s10796-021-10141-9⟩
As Machine Learning (ML) is now widely applied in many domains, in both research and industry, an understanding of what is happening inside the black box is becoming a growing demand, especially by non-experts of these models. Several approaches had
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::77ef4c02fee244a3aa7ded443b0e731f
https://hal.archives-ouvertes.fr/hal-03259008/document
https://hal.archives-ouvertes.fr/hal-03259008/document