Artificial Intelligence in Medicine

Machine Learning and Deep Learning.- Survival Hierarchical Agglomerative Clustering: A Semi-Supervised Clustering Method Incorporating Survival Data.- Boosted Random Forests for Predicting Treatment Failure of Chemotherapy Regimens.- A Binning Approach for Predicting Long-Term Prognosis in Multiple Sclerosis.- Decision Tree Approaches to Select High Risk Patients for Lung Cancer Screening based on the UK Primary Care Data.- Causal Discovery with Missing Data in a Multicentric Clinical Study.- Novel approach for phenotyping based on diverse top-k subgroup lists.- Patient Event Sequences for Predicting Hospitalization Length of Stay.- Autoencoder-based prediction of ICU clinical codes.- Explainability and Transfer Learning.- Hospital Length of Stay Prediction Based on Multi-modal Data towards Trustworthy Human-AI Collaboration in Radiomics.- Explainable Artificial Intelligence for Cytological Image Analysis.- Federated Learning to Improve Counterfactual Explanations for Sepsis Treatment Prediction.- Explainable AI for Medical Event Prediction for Heart Failure Patients.- Adversarial Robustness and Feature Impact Analysis for Driver Drowsiness Detection.- Computational Evaluation of Model-Agnostic Explainable AI using Local Feature Importance in Healthcare.- Batch Integrated Gradients: Explanations for Temporal Electronic Health Records.- Improving stroke trace classification explainability through counterexamples.- Spatial Knowledge Transfer with Deep Adaptation Network for Predicting Hospital Readmission.- Dealing with Data Scarcity in Rare Diseases: Dynamic Bayesian Networks and Transfer Learning to Develop Prognostic Models of Amyotrophic Lateral Sclerosis.- Natural Language Processing.- A Rule-free Approach for Cardiological Registry Filling from Italian Clinical Notes with Question Answering Transformers.- Classification of Fall Types in Parkinson Disease From Self-report Data Using Natural Language Processing.- BERT for complex systematic review screening to support the future of medical research.- GGTWEAK: Gene Tagging with Weak Supervision for German Clinical Text.- Soft-prompt tuning to predict lung cancer using primary care free-text Dutch medical notes.- Machine learning models for automatic Gene Ontology annotation of biological texts.- Image Analysis and Signal Analysis.- A Robust BKSVD Method for Blind Color Deconvolution and Blood Detection on H&E Histological Images.- Can knowledge transfer techniques compensate for the limited myocardial infarction data by leveraging hemodynamics? An in silico Study.- Covid-19 Diagnosis In 3D Chest CT Scans With Attention-Based Models.- Generalized Deep Learning-based Proximal Gradient Descent for MR Reconstruction.- Crowdsourcing segmentation of histopathological images using annotations provided by medical students.- Automatic sleep stage classification on EEG signals using time-frequency representation.- Learning EKG Diagnostic Models with Hierarchical Class Label Dependencies.- Discriminant audio properties in deep learning based respiratory insufficiency detection in Brazilian Portuguese.- ECGAN: Self-supervised generative adversarial network for electrocardiography.- Data Analysis and Statistical Models.- Nation-wide ePrescription Data Reveals Landscape of Physicians and their Drug Prescribing Patterns in Slovenia.- Machine Learning Based Prediction of Incident Cases of Crohns Disease Using Electronic Health Records from a Large Integrated Health System.- Prognostic prediction of paediatric DHF in two hospitals in Thailand.- The Impact of Bias on Drift Detection in AI Health Software.- A Topological Data Analysis Framework for Computational Phenotyping.- Ranking of Survival-Related Gene Sets through Integration of Single-Sample Gene Set Enrichment and Survival Analysis.- Knowledge Representation and Decision Support.- Supporting the prediction of AKI evolution through interval-based