Alle Papers – Machine Learning im Gesundheitswesen

Expert Level Evaluations for Explainable AI (XAI) Methods in the Medical Domain

RETRACTED ARTICLE: Feature optimization by discrete weights for heart disease prediction using supervised learning

The role of artificial intelligence in identifying asthma in pediatric inpatient setting

Patient-centered care and the electronic health record: exploring functionality and gaps

A multi-center study on the adaptability of a shared foundation model for electronic health records

Predicting mortality and hospitalization in heart failure using machine learning: A systematic literature review

Systematic Review of Clinical Prediction Rules for Neuroimaging in the Evaluation of Dementia

A flexible framework for recognizing events, temporal expressions, and temporal relations in clinical text

A multi-class classification model for supporting the diagnosis of type II diabetes mellitus

Explainable Machine Learning to Predict Successful Weaning Among Patients Requiring Prolonged Mechanical Ventilation: A Retrospective Cohort Study in Central Taiwan

Detection of COVID-19 findings by the local interpretable model-agnostic explanations method of types-based activations extracted from CNNs

B-LIME: An Improvement of LIME for Interpretable Deep Learning Classification of Cardiac Arrhythmia from ECG Signals

DEPLOYR: a technical framework for deploying custom real-time machine learning models into the electronic medical record

Large language models for data extraction from unstructured and semi-structured electronic health records: a multiple model performance evaluation

Machine Learning for Mortality Analysis in Patients with COVID-19

Sliced-Wasserstein Flows: Nonparametric Generative Modeling via Optimal\n Transport and Diffusions

Explainable Prediction of Medical Codes from Clinical Text

Accelerated forgetting in Alzheimer-type dementia

Multimodal diagnosis model of Alzheimer’s disease based on improved Transformer

Role of deep learning in early detection of COVID-19: Scoping review

Prediction of Autopsy Verified Neuropathological Change of Alzheimer’s Disease Using Machine Learning and MRI

Leveraging natural language processing to augment structured social determinants of health data in the electronic health record

A Semi-Supervised Multi-Task Learning Approach for Predicting Short-Term Kidney Disease Evolution

Semantic Web Technologies for Explainable Machine Learning Models: A Literature Review.

An evaluation of synthetic data augmentation for mitigating covariate bias in health data