2021-11-02Zeitschriftenartikel
Machine Learning for Health: Algorithm Auditing & Quality Control
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; Kazim, Emre; Koshiyama, Adriano; Piechottka, Sven; Macpherson, Sheena; Shadforth, Ian; Geierhofer, Regina; Matek, Christian; Krois, Joachim; Sanguinetti, Bruno; Arentz, Matthew; Bielik, Pavol; Calderon‑Ramirez, Saul; Abbood, Auss; Langer, Nicolas; Haufe, Stefan; Kherif, Ferath; Pujari, Sameer; Samek, Wojciech; Wiegand, Thomas
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 ...