Alle Papers – Machine Learning im Gesundheitswesen

Equivariant Hamiltonian Flows

"The survival kit-V3.0". A package for large analyses of survival data

Textual inference for eligibility criteria resolution in clinical trials

Gromov-Wasserstein Guided Representation Learning for Cross-Domain Recommendation

Prediction of obstetrical and fetal complications using automated electronic health record data

An architecture for a continuous, user-driven, and data-driven application of clinical guidelines and its evaluation

Predictive ability of current machine learning algorithms for type 2 diabetes mellitus: A meta‐analysis

Developing machine learning models for prediction of mortality in the medical intensive care unit

Integrating artificial intelligence into healthcare systems: more than just the algorithm

Coronary Risk Estimation Based on Clinical Data in Electronic Health Records

Optimized One vs One Approach in Multiclass Classification for Early Alzheimer’s Disease and Mild Cognitive Impairment Diagnosis

Construct validity of six sentiment analysis methods in the text of encounter notes of patients with critical illness

AI-MARRVEL — A Knowledge-Driven AI System for Diagnosing Mendelian Disorders

Computerized techniques pave the way for drug-drug interaction prediction and interpretation

Factors Affecting the Accuracy of Prediction Models Limit the Comparison of Rival Prediction Models When Applied to Separate Data Sets

Artificial Intelligence Models in the Diagnosis of Adult-Onset Dementia Disorders: A Review

An end-to-end hybrid algorithm for automated medication discrepancy detection

Large language models: a new chapter in digital health

Finding falls in ambulatory care clinical documents using statistical text mining

Significance of Visible Non-Invasive Risk Attributes for the Initial Prediction of Heart Disease Using Different Machine Learning Techniques

Analyzing categorical information in two publicly available drug terminologies: RxNorm and NDF-RT

Machine learning approach on healthcare big data: a review

Learning the natural history of human disease with generative transformers

Kinematics of Big Biomedical Data to characterize temporal variability and seasonality of data repositories: Functional Data Analysis of data temporal evolution over non-parametric statistical manifolds

Bayesian networks for patient monitoring