Alle Papers – Machine Learning im Gesundheitswesen

Utilizing Explainable Artificial Intelligence to Address Deep Learning in Biomedical Domain

Explainable Artificial Intelligence: An Updated Perspective

Challenges in creating an opt-in biobank with a registrar-based consent process and a commercial EHR

Comparison of Temporal and Non-Temporal Features Effect on Machine Learning Models Quality and Interpretability for Chronic Heart Failure Patients

Heart Disease Prediction Using Machine Learning

Big Data in Medizin und Gesundheitswesen

Deep learning in multimedia healthcare applications: a review

AI-Powered early warning systems for clinical deterioration significantly improve patient outcomes: a meta-analysis

A Novel AI-based chatbot Application for Personalized Medical Diagnosis and review using Large Language Models

Clinical trials informed framework for real world clinical implementation and deployment of artificial intelligence applications

Information Extraction for Tracking Liver Cancer Patients' Statuses: From Mixture of Clinical Narrative Report Types

Machine Learning and Deep Learning for the Pharmacogenomics of Antidepressant Treatments

Fusion of sequential visits and medical ontology for mortality prediction

Computer processing of DNA sequence data

Artificial Intelligence in Medicine

Text Dialogue Analysis for Primary Screening of Mild Cognitive Impairment: Development and Validation Study

Measuring the quality and completeness of medication-related information derived from hospital electronic health records database

Analysis of Clinical Decision Support System in Healthcare Industry Using Machine Learning Approach

Subtyping of psychiatric patients by cluster analysis of QEEG

Knowledge graph enrichment from clinical narratives using NLP, NER, and biomedical ontologies for healthcare applications

Identifying Possible False Matches in Anonymized Hospital Administrative Data without Patient Identifiers

Automatic infection detection based on electronic medical records

The Rise of GPT-3: Implications for Natural Language Processing and Beyond

Hybrid approach to the generation of medical guidelines for insulin therapy for children

Using Computational Approaches to Improve Risk-Stratified Patient Management: Rationale and Methods