Explainable Artificial Intelligence and Process Mining Applications for Healthcare

.- International Workshop on Explainable Artificial Intelligence in Healthcare. .- Enabling Visual and Textual Explanation in Diagnostics: A Federated Learning Approach with Medical Vision-Language Models. .- A User-Centric Analysis of Explainability in AI-Based Medical Image Diagnosis. .- Spot the Relevance: Evaluating Pixel Attribution Methods for Clinical Significance in Radiological Imaging. .- Evaluating LIME and SHAP under Class Imbalance: A Lung Cancer Prediction Case Study using CPRD data. .- Explainable Artificial Intelligence in Speech-Based Cognitive Decline Detection: A Systematic Review. .- Cancer Care Needs Explainable Artificial Intelligence: Motivations from Potential Users. .- Data-centric explanation methods for healthcare professionals. .- International Workshop on Process Mining applications for Healthcare. .- Predictive Process Monitoring for the Next Activities in Clinical Pathways. .- Towards Automated Compliance Checking for Care Trajectories: Process Extraction Using Large Language Models. .- Predicting Next Clinical Event in Amyotrophic Lateral Sclerosis using Process-Oriented Machine Learning Models: a Case Study. .- A Novel Way to Evaluate Medical Discharge Predictions, a research paper. .- Transforming Event Logs into Narrative Texts for Outcome Prediction: A Case Study in a Hospital Emergency Department. .- Federated I-PALIA: Privacy-By-Design Distributed Process Discovery for Duplicated Activities in Healthcare. .- From XAI-Driven Decision Paths to Processes: Mining and Clustering Decision Paths for Interpretable Kidney Transplant Prediction.