Alle Papers – Machine Learning im Gesundheitswesen

Transforming Healthcare Education: Harnessing Large Language Models for Frontline Health Worker Capacity Building using Retrieval-Augmented Generation

<p>Risk Prediction of Dyslipidemia for Chinese Han Adults Using Random Forest Survival Model</p>

Performance of Multiple Pretrained BERT Models to Automate and Accelerate Data Annotation for Large Datasets

A survey on semanticized and personalized health recommender systems

Random-effects models for diagnostic accuracy data.

Deconstructing the diagnostic reasoning of human versus artificial intelligence

Comparing ascertainment of chronic condition status with problem lists versus encounter diagnoses from electronic health records

ChatGPT: Transforming Healthcare with AI

Electronic health records systems and hospital clinical performance: a study of nationwide hospital data

The readiness of SNOMED problem list concepts for meaningful use of electronic health records

Predicting seizure recurrence after an initial seizure-like episode from routine clinical notes using large language models: a retrospective cohort study

De-identification of patient notes with recurrent neural networks

Framework for personalized prediction of treatment response in relapsing remitting multiple sclerosis

Machine Learning to Predict Mortality and Critical Events in COVID-19 Positive New York City Patients

ICU Survival Prediction Incorporating Test-Time Augmentation to Improve the Accuracy of Ensemble-Based Models

Auto IV: Counterfactual Prediction via Automatic Instrumental Variable Decomposition

Comparison of Prompt Engineering and Fine-Tuning Strategies in Large Language Models in the Classification of Clinical Notes

User-Centric Explainability in Healthcare: A Knowledge-Level Perspective of Informed Machine Learning

Prediction of mortality in an intensive care unit using logistic regression and a hidden Markov model

Hi-Le and HiTCLe: Ensemble Learning Approaches for Early Diabetes Detection Using Deep Learning and Explainable Artificial Intelligence

Artificial intelligence and leukocyte epigenomics: Evaluation and prediction of late-onset Alzheimer’s disease

Utilizing BERT for biomedical and clinical text mining

Assessing Schizophrenia Patients Through Linguistic and Acoustic Features Using Deep Learning Techniques

Hybrid disease prediction approach leveraging digital twin and metaverse technologies for health consumer

Reducing PSA-Based Prostate Cancer Screening in Men Aged 75 Years and Older with the Use of Highly Specific Computerized Clinical Decision Support