Alle Papers – Machine Learning im Gesundheitswesen

Using machine learning to detect problems in ECG data collection

Comparative analysis of machine learning models for coronary artery disease prediction with optimized feature selection

Retrieval-Augmented Generation (RAG) in Healthcare: A Comprehensive Review

Learning temporal weights of clinical events using variable importance

rEHR: An R package for manipulating and analysing Electronic Health Record data

Performance overview of an artificial intelligence in biomedics: a systematic approach

Automated physician order recommendations and outcome predictions by data-mining electronic medical records.

Predicting Hospitalization Due to COPD Exacerbations in Swedish Primary Care Patients Using Machine Learning – Based on the ARCTIC Study

CORE-GPT: Combining Open Access Research and Large Language Models for Credible, Trustworthy Question Answering

A Genetics-Based Machine Learning Approach to Knowledge Discovery in Clinical Data.

GraphXAI: a survey of graph neural networks (GNNs) for explainable AI (XAI)

The Effect of the Intelligent Sepsis Management System on Outcomes among Patients with Sepsis and Septic Shock Diagnosed According to the Sepsis-3 Definition in the Emergency Department

Data Mining on ICU Mortality Prediction Using Early Temporal Data: A Survey

Measures of prediction error for survival data with longitudinal covariates

Graph-Guided Network for Irregularly Sampled Multivariate Time Series

Evaluating Model Robustness and Stability to Dataset Shift

An ANFIS perspective for the diagnosis of type II diabetes

Leveraging Shapley Additive Explanations for Feature Selection in Ensemble Models for Diabetes Prediction

Detecting Diseases by Human-Physiological-Parameter-Based Deep Learning

Diagnosing post-traumatic stress disorder using electronic medical record data

Heterogeneous Multi-Task Learning With Expert Diversity

Biomedical event trigger detection by dependency-based word embedding

Explainable AI (XAI) Applied in Machine Learning for Pain Modeling: A Review

Outcome Prediction in Clinical Treatment Processes

Unveiling New Strategies Facilitating the Implementation of Artificial Intelligence in Neuroimaging for the Early Detection of Alzheimer’s Disease