Alle Papers – Machine Learning im Gesundheitswesen

Bibliometric analysis on the adoption of artificial intelligence applications in the e-health sector

Learning Hierarchical Features from Generative Models

Learn-Explain-Reinforce: Counterfactual Reasoning and its Guidance to Reinforce an Alzheimer's Disease Diagnosis Model

Interpretable deep learning architecture for gastrointestinal disease detection: A Tri-stage approach with PCA and XAI

Optimal survival trees

Predicting Infections Using Computational Intelligence – A Systematic Review

Multimodal and multicontrast image fusion via deep generative models

In simulated data and health records, latent class analysis was the optimum multimorbidity clustering algorithm

Deep ensemble multitask classification of emergency medical call incidents combining multimodal data improves emergency medical dispatch

Multimorbidity in Medicare Beneficiaries: Performance of an ICD‐Coded Multimorbidity‐Weighted Index

Graph Triple-Attention Network for Disease-Related LncRNA Prediction

Multi-scale multimodal deep learning framework for Alzheimer's disease diagnosis

Additive MIL: Intrinsically Interpretable Multiple Instance Learning for Pathology

Efficient analysis of COVID-19 clinical data using machine learning models

Diagnostic Inferencing via Improving Clinical Concept Extraction with Deep Reinforcement Learning: A Preliminary Study

Extension of the Hepar II Model to Multiple-Disorder Diagnosis

AnomiGAN: Generative Adversarial Networks for Anonymizing Private Medical Data

Artificial Intelligence in Medicine

The Salzburg Intensive Care database (SICdb): an openly available critical care dataset

Dealing with missing data, small sample sizes, and heterogeneity in machine learning studies of brain disorders

A Computational Platform Integrating a Mechanistic Model of Crohn’s Disease for Predicting Temporal Progression of Mucosal Damage and Healing

Automated electronic reminders to facilitate primary cardiovascular disease prevention: randomised controlled trial

Learning and inference in knowledge-based probabilistic model for medical diagnosis

Comparison of machine learning approaches for enhancing Alzheimer’s disease classification

Predicting bloodstream infection outcome using machine learning