arXiv (Cornell University)
Improving Model's Interpretability and Reliability using Biomarkers
February 2024 • Gautam Rajendrakumar Gare, Tom Fox, Beam Chansangavej, Amita Krishnan, Ricardo Luis Rodriguez, Bennett P. deBoisblanc, Deva Ramanan, John Galeotti
Accurate and interpretable diagnostic models are crucial in the safety-critical field of medicine. We investigate the interpretability of our proposed biomarker-based lung ultrasound diagnostic pipeline to enhance clinicians' diagnostic capabilities. The objective of this study is to assess whether explanations from a decision tree classifier, utilizing biomarkers, can improve users' ability to identify inaccurate model predictions compared to conventional saliency maps. Our findings demonstrate that decision tree…