Alle Papers – Machine Learning im Gesundheitswesen

Evidential MACE prediction of acute coronary syndrome using electronic health records

Automated Detection of Sepsis Using Electronic Medical Record Data: A Systematic Review

Developing a portable natural language processing based phenotyping system

Optimized Risk Scores

Dynamic survival prediction in intensive care units from heterogeneous time series without the need for variable selection or curation

Enhancing Dialogue Symptom Diagnosis with Global Attention and Symptom Graph

Safe Medicine Recommendation via Medical Knowledge Graph Embedding

Multimorbidity patterns and 18‐year transitions from normal cognition to dementia and death: A population‐based study

DeepCOVID: An Operational Deep Learning-driven Framework for Explainable Real-time COVID-19 Forecasting

Comparative Evaluation of Advanced AI Reasoning Models in Pediatric Clinical Decision Support: ChatGPT O1 vs. DeepSeek-R1

What does validation of cases in electronic record databases mean? The potential contribution of free text

EXPERIENCE WITH BAYE'S THEOREM FOR COMPUTER DIAGNOSIS OF CONGENITAL HEART DISEASE*

Detecting Hypoglycemia Incidents Reported in Patients’ Secure Messages: Using Cost-Sensitive Learning and Oversampling to Reduce Data Imbalance

Implementation of machine learning algorithms to create diabetic patient re-admission profiles

A Derivation of the Pythagorean Won-Loss Formula in Baseball

A clinical deep learning framework for continually learning from cardiac signals across diseases, time, modalities, and institutions

Feasibility of Prioritizing Drug–Drug-Event Associations Found in Electronic Health Records

Proof of Disease: A Blockchain Consensus Protocol for Accurate Medical Decisions and Reducing the Disease Burden

Validating an ontology-based algorithm to identify patients with Type 2 Diabetes Mellitus in Electronic Health Records

Predicting Therapy Success and Costs for Personalized Treatment Recommendations Using Baseline Characteristics: Data-Driven Analysis

Graph neural networks with global noise filtering for session-based recommendation

EHR-Oriented Knowledge Graph System: Toward Efficient Utilization of Non-Used Information Buried in Routine Clinical Practice

Comparing predictions made by a prediction model, clinical score, and physicians

Combining Free Text and Structured Electronic Medical Record Entries to Detect Acute Respiratory Infections

A general approach for improving deep learning-based medical relation extraction using a pre-trained model and fine-tuning