El. knyga: Trustworthy Machine Learning for Healthcare: First International Workshop, TML4H 2023, Virtual Event, May 4, 2023, Proceedings

Do Tissue Source Sites leave identifiable Signatures in Whole Slide Images beyond staining?.- Explaining Multiclass Classifiers with Categorical Values: A Case Study in Radiography.- Privacy-preserving machine learning for healthcare: open challenges and future perspectives.- Self-Supervised Predictive Coding with Multimodal Fusion for Patient Deterioration Prediction in Fine-grained Time Resolution. Safe Exploration in Dose Finding Clinical Trials with Heterogeneous Participants. Isabel Chien, Javier Gonzalez Hernandez, Richard E Turner.- CGXplain: Rule-Based Deep Neural Network Explanations Using Dual Linear Programs.- ExBEHRT: Extended Transformer for Electronic Health Records.- Stasis: Reinforcement Learning Simulators for Human-Centric Real-World Environments. Cross-domain Microscopy Cell Counting by Disentangled Transfer Learning.- Post-hoc Saliency Methods Fail to Capture Latent Feature Importance in Time Series Data.- Enhancing Healthcare Model Trustworthiness through Theoretically Guaranteed One-Hidden-Layer CNN Purification.- A Kernel Density Estimation based Quality Metric for Quality Assessment of Obstetric Ultrasound Video.- Learn2Agree: Fitting with Multiple Annotators without Objective Ground Truth.- Conformal Prediction Masks: Visualizing Uncertainty in Medical Imaging.- Why Deep Surgical Models Fail?: Revisiting Surgical Action Triplet Recognition through the Lens of Robustness.- Geometry-Based end-to-end Segmentation of Coronary artery ib Computed Tomography Angiograph.