Alle Papers – Machine Learning im Gesundheitswesen

Assessing the accuracy of an inter-institutional automated patient-specific health problem list

Towards artificial intelligence-based learning health system for population-level mortality prediction using electrocardiograms

Chat GPT in Tailoring Individualized Lifestyle-Modification Programs in Metabolic Syndrome: Potentials and Difficulties?

A study of factors related to patients’ length of stay using data mining techniques in a general hospital in southern Iran

Development and validation of an epidemiologic case definition of epilepsy for use with routinely collected Australian health data

ChatGPT for digital pathology research

Strategies to Turn Real-world Data Into Real-world Knowledge

A Predictive Text System for Medical Recommendations in Telemedicine: A Deep Learning Approach in the Arabic Context

Using machine learning approach to predict depression and anxiety among patients with epilepsy in China: A cross-sectional study

Cardiac Failure Forecasting Based on Clinical Data Using a Lightweight Machine Learning Metamodel

Predicting cardiovascular risk with hybrid ensemble learning and explainable AI

Reflections and attentiveness on eXplainable Artificial Intelligence (XAI). The journey ahead from criticisms to human–AI collaboration

Scientific Evidence for Clinical Text Summarization Using Large Language Models: Scoping Review

The Dangers of Post-hoc Interpretability: Unjustified Counterfactual Explanations

Exploring new possibilities for case-based explanation of artificial neural network ensembles

Early Analysis and Prediction of Fetal Abnormalities Using Machine Learning Classifiers

Using electronic health record data for clinical research: a quick guide

Discovering hospital admission patterns using models learnt from electronic hospital records

Modelling the prevalence of diabetes mellitus risk factors based on artificial neural network and multiple regression

Lipschitz Recurrent Neural Networks

Handling Temporality of Clinical Events for Drug Safety Surveillance.

Discrete-time survival analysis in the critically ill: a deep learning approach using heterogeneous data

Integration of AI in Healthcare Systems — A Discussion of the Challenges and Opportunities of Integrating AI in Healthcare Systems for Disease Detection and Diagnosis

Leveraging electronic health records data to predict multiple sclerosis disease activity

Machine learning based multi-modal prediction of future decline toward Alzheimer’s disease: An empirical study