Alle Papers – Machine Learning im Gesundheitswesen

Automatic mining of symptom severity from psychiatric evaluation notes

A time series continuous missing values imputation method based on generative adversarial networks

Automated Feature Selection of Predictors in Electronic Medical Records Data

A new approach for interpretability and reliability in clinical risk prediction: Acute coronary syndrome scenario

Future of evidence ecosystem series: 2. current opportunities and need for better tools and methods

Computable knowledge: An imperative for Learning Health Systems

Diagnostic accuracy of an artificial intelligence online engine in migraine: A multi‐center study

An Explainable Convolutional Neural Network for the Early Diagnosis of Alzheimer’s Disease from 18F-FDG PET

Prediction of COVID-19 Hospital Length of Stay and Risk of Death Using Artificial Intelligence-Based Modeling

Machine Learning Outperforms Existing Clinical Scoring Tools in the Prediction of Postoperative Atrial Fibrillation During Intensive Care Unit Admission After Cardiac Surgery

Identifying vulnerable older adult populations by contextualizing geriatric syndrome information in clinical notes of electronic health records

A Novel Expert System for the Diagnosis and Treatment of Heart Disease

Cascading and Ensemble Techniques in Deep Learning

Direct estimation of cause-specific mortality fractions from verbal autopsies: multisite validation study using clinical diagnostic gold standards

VetTag: improving automated veterinary diagnosis coding via large-scale language modeling

Early detection of dementia through retinal imaging and trustworthy AI

The application of artificial intelligence in health financing: a scoping review

Introduction to the Seventh Annual Lifelog Search Challenge, LSC'24

ANMerge: A Comprehensive and Accessible Alzheimer’s Disease Patient-Level Dataset

A Novel Deep Learning–Based System for Triage in the Emergency Department Using Electronic Medical Records: Retrospective Cohort Study

Reducing surgical patient costs through use of an artificial neural network to predict transfusion requirements

HeartEnsembleNet: An Innovative Hybrid Ensemble Learning Approach for Cardiovascular Risk Prediction

“Big Data” in Laboratory Medicine

Phenotypic Disease Network Analysis to Identify Comorbidity Patterns in Hospitalized Patients with Ischemic Heart Disease Using Large-Scale Administrative Data

Practical Strategies for Extreme Missing Data Imputation in Dementia Diagnosis