Alle Papers – Machine Learning im Gesundheitswesen

A machine learning model for predicting deterioration of COVID-19 inpatients

EHRAgent: Code Empowers Large Language Models for Few-shot Complex Tabular Reasoning on Electronic Health Records

Temporal phenotyping of medically complex children via PARAFAC2 tensor factorization

A comparison between discrete and continuous time Bayesian networks in learning from clinical time series data with irregularity

Development of an openEHR Template for COVID-19 Based on Clinical Guidelines

Developing a short-term prediction model for asthma exacerbations from Swedish primary care patients’ data using machine learning - Based on the ARCTIC study

MC-RVAE: Multi-channel recurrent variational autoencoder for multimodal Alzheimer’s disease progression modelling

The development and evaluation of a computerized decision aid for the treatment of psychotic disorders

Learning Adaptive Forecasting Models from Irregularly Sampled Multivariate Clinical Data

Diabetes Prediction Using Machine Learning Techniques

Extracting Features from Time Series

A Large Language Model Screening Tool to Target Patients for Best Practice Alerts: Development and Validation

Will Machine Learning Enable Us to Finally Cut the Gordian Knot of Schizophrenia

Diarec: Dynamic Intention-Aware Recommendation with Attention-Based Context-Aware Item Attributes Modeling

Patient classification and outcome prediction in IgA nephropathy

An effective density-based clustering and dynamic maintenance framework for evolving medical data streams

Ontology-based venous thromboembolism risk assessment model developing from medical records

A Framework for Usable and Effective Clinical Decision Support: Experience from the iCPR Randomized Clinical Trial

Using Predictive Modeling and Machine Learning to Identify Patients Appropriate for Outpatient Anterior Cervical Fusion and Discectomy

Kidney Impairment Prediction Due to Diabetes Using Extended Ensemble Learning Machine Algorithm

Local vs. Global Interpretability of Machine Learning Models in Type 2 Diabetes Mellitus Screening

Privacy-preserving federated neural network learning for disease-associated cell classification

Data-Driven Information Extraction from Chinese Electronic Medical Records

Clinical prediction models to predict the risk of multiple binary outcomes: a comparison of approaches

Linking Ambulance Records with Hospital and Death Index Data to Evaluate Patient Outcomes