Machine Learning for Health: Algorithm Auditing & Quality Control.

Developers proposing new machine learning for health (ML4H) tools often pledge to match or even surpass the performance of existing tools, yet the reality is usually more complicated. Reliable deployment of ML4H to the real world is challenging as examples from diabetic retinopathy or Covid-19 scree...

Descripción completa

Detalles Bibliográficos

Publicado en:	Journal of Medical Systems Vol. 45; no. 12; pp. 1 - 9
Autores principales:	Oala, Luis, Murchison, Andrew G., Balachandran, Pradeep, Choudhary, Shruti, Fehr, Jana, Leite, Alixandro Werneck, Goldschmidt, Peter G., Johner, Christian, Schörverth, Elora D. M., Nakasi, Rose, Meyer, Martin, Cabitza, Federico, Baird, Pat, Prabhu, Carolin, Weicken, Eva, Liu, Xiaoxuan, Wenzel, Markus, Vogler, Steffen, Akogo, Darlington, Alsalamah, Shada
Formato:	editorial tables/charts Journal Article
Publicado:	Springer Nature Dec2021
Acceso en línea:	Ver este registro en EBSCOhost