Alle Papers – Machine Learning im Gesundheitswesen

On local anomaly detection and analysis for clinical pathways

Using uncertainty to link and rank evidence from biomedical literature for model curation

Leveraging Large-Scale Electronic Health Records and Interpretable Machine Learning for Clinical Decision Making at the Emergency Department: Protocol for System Development and Validation

Bayesian networks for clinical decision support: A rational approach to dynamic decision-making under uncertainty

Generative artificial intelligence: synthetic datasets in dentistry

The Camden & Islington Research Database: Using electronic mental health records for research

Prediction for chronic kidney disease by categorical and non_categorical attributes using different machine learning algorithms

Predicting patient acuity from electronic patient records

TASTE

Healthcare Data Mining: Prediction Inpatient Length of Stay

Hepatitis B Diagnosis Using Logical Inference And Generalized Regression Neural Networks

Explaining the output of ensembles in medical decision support on a case by case basis

Big Data analysis to improve care for people living with serious illness: The potential to use new emerging technology in palliative care

TriNetX and Real-World Evidence: A Critical Review of Its Strengths, Limitations, and Bias Considerations in Clinical Research

Support Vector Machines for Differential Prediction

Predicting Readmission or Death After Discharge From the ICU: External Validation and Retraining of a Machine Learning Model

RAPT: Pre-training of Time-Aware Transformer for Learning Robust Healthcare Representation

Health Multimedia

Can I Trust the Explainer? Verifying Post-hoc Explanatory Methods

Integration of cardiovascular risk assessment with COVID-19 using artificial intelligence

Hybrid Deep Learning for Medication-Related Information Extraction From Clinical Texts in French: MedExt Algorithm Development Study

Subunit structure of myosin, II. Heavy and light alkali components.

A Comprehensive Survey of Small Language Models in the Era of Large Language Models: Techniques, Enhancements, Applications, Collaboration with LLMs, and Trustworthiness

Using artificial intelligence and predictive modelling to enable learning healthcare systems (LHS) for pandemic preparedness

Application of multi-label classification models for the diagnosis of diabetic complications