Machine learning with asymmetric abstention for biomedical decision-making

Machine learning and artificial intelligence have entered biomedical decision-making for diagnostics, prognostics, or therapy recommendations. However, these methods need to be interpreted with care because of the severe consequences for patients. In contrast to human decision-making, computational...

Descripción completa

Detalles Bibliográficos
Autores principales: Gandouz, Mariem, Holzmann, Hajo, Heider, Dominik
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8549182/
https://www.ncbi.nlm.nih.gov/pubmed/34702225
http://dx.doi.org/10.1186/s12911-021-01655-y

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8549182/
https://www.ncbi.nlm.nih.gov/pubmed/34702225
http://dx.doi.org/10.1186/s12911-021-01655-y

Ejemplares similares