32 citations · 37 across the 3 of their papers we have counts for
3 papers
cs.LG2022★ 32 cited
A novel interpretable machine learning system to generate clinical risk scores: An application for predicting early mortality or unplanned readmission in a retrospective cohort study
Yilin Ning, Siqi Li, Marcus Eng Hock Ong +4
Risk scores are widely used for clinical decision making and commonly generated from logistic regression models. Machine-learning-based methods may work well for identifying import…
cs.LG2021★ 2 cited
Shapley variable importance clouds for interpretable machine learning
Yilin Ning, Marcus Eng Hock Ong, Bibhas Chakraborty +4
Interpretable machine learning has been focusing on explaining final models that optimize performance. The current state-of-the-art is the Shapley additive explanations (SHAP) that…
cs.CV2019★ 3 cited
Multi-Instance Multi-Scale CNN for Medical Image Classification
Shaohua Li, Yong Liu, Xiuchao Sui +4
Deep learning for medical image classification faces three major challenges: 1) the number of annotated medical images for training are usually small; 2) regions of interest (ROIs)…