1 code implementation • 10 Nov 2022 • Vien Ngoc Dang, Anna Cascarano, Rosa H. Mulder, Charlotte Cecil, Maria A. Zuluaga, Jerónimo Hernández-González, Karim Lekadir
Here, we present a systematic study of bias in ML models designed to predict depression in four different case studies covering different countries and populations.
no code implementations • 26 Apr 2018 • Iker Beñaran-Muñoz, Jerónimo Hernández-González, Aritz Pérez
In this paper, the use of candidate labeling for crowd learning is proposed, where the annotators may provide more than a single label per instance to try not to miss the real label.