no code implementations • 3 Oct 2023 • Xianjing Liu, Bo Li, Meike W. Vernooij, Eppo B. Wolvius, Gennady V. Roshchupkin, Esther E. Bron
AI has greatly enhanced medical image analysis, yet its use in epidemiological population imaging studies remains limited due to visualization challenges in non-linear models and lack of confounder control.
1 code implementation • 25 Jun 2021 • Xianjing Liu, Bo Li, Esther Bron, Wiro Niessen, Eppo Wolvius, Gennady Roshchupkin
Confounding bias is a crucial problem when applying machine learning to practice, especially in clinical practice.
no code implementations • WS 2018 • Mingkuan Liu, Musen Wen, Selcuk Kopru, Xianjing Liu, Alan Lu
To tackle this challenge, in this paper, we propose a semi-supervised learning method to utilize unlabeled data and user feedback signals to improve the performance of ML models.