Alle Papers – Machine Learning im Gesundheitswesen

Changes in Electronic Health Record Use Time and Documentation over the Course of a Decade

Deep learning based low-cost high-accuracy diagnostic framework for dementia using comprehensive neuropsychological assessment profiles

RadioLOGIC, a healthcare model for processing electronic health records and decision-making in breast disease

Justifying Arabic Text Sentiment Analysis Using Explainable AI (XAI): LASIK Surgeries Case Study

Artificial intelligence in outcomes research: a systematic scoping review

Transformer- and Generative Adversarial Network–Based Inpatient Traditional Chinese Medicine Prescription Recommendation: Development Study

Early short-term prediction of emergency department length of stay using natural language processing for low-acuity outpatients

Ensemble-GNN: federated ensemble learning with graph neural networks for disease module discovery and classification

Leveraging Brain Modularity Prior for Interpretable Representation Learning of fMRI

Detection of Alzheimer's disease using deep learning models: A systematic literature review

A weighted multi-feature transfer learning framework for intelligent medical decision making

Artificial Intelligence

Machine learning-aided risk prediction for metabolic syndrome based on 3 years study

An Optimized Machine Learning Model Accurately Predicts In-Hospital Outcomes at Admission to a Cardiac Unit

ISeeU2: Visually interpretable mortality prediction inside the ICU using deep learning and free-text medical notes

A Link to Improve Stroke Patient Care: A Successful Linkage Between a Statewide Emergency Medical Services Data System and a Stroke Registry

Information Technology in PBRNs: The Indiana University Medical Group Research Network (IUMG ResNet) Experience

Suicidal Trend Analysis of Twitter Using Machine Learning and Neural Network

Gradient Boosting Based Model for Elderly Heart Failure, Aortic Stenosis, and Dementia Classification

Time pattern reconstruction for classification of irregularly sampled time series

Identification of Variable Importance for Predictions of Mortality From COVID-19 Using AI Models for Ontario, Canada

Efficient and Explainable Risk Assessments for Imminent Dementia in an Aging Cohort Study

Estimating Effective Connectivity by Recurrent Generative Adversarial Networks

LIMEtree: Interactively Customisable Explanations Based on Local Surrogate Multi-output Regression Trees

D4: a Chinese Dialogue Dataset for Depression-Diagnosis-Oriented Chat