Alle Papers – Machine Learning im Gesundheitswesen

The formal requirements of algorithms and their implications in clinical medicine and quality management

Dementia prediction in the general population using clinically accessible variables: a proof-of-concept study using machine learning. The AGES-Reykjavik study

Enriching representation learning using 53 million patient notes through human phenotype ontology embedding

Linking Free Text Documentation of Functioning and Disability to the ICF With Natural Language Processing

Sortal anaphora resolution to enhance relation extraction from biomedical literature

Towards Explainable Representation of Time-Evolving Graphs via Spatial-Temporal Graph Attention Networks

Enhancing Diagnosis Through Technology

Fidelity of Medical Reasoning in Large Language Models

Intelligence artificielle : une introduction pour les cliniciens

Multi-diseases Classification from Chest-X-ray: A Federated Deep Learning Approach

Medication Extraction from Electronic Clinical Notes in an Integrated Health System: A Study on Aspirin Use in Patients with Nonvalvular Atrial Fibrillation

Comparison between machine learning methods for mortality prediction for sepsis patients with different social determinants

A Reinforcement Learning-Informed Pattern Mining Framework for Multivariate Time Series Classification

Medical Diagnosis from a Clinician’s Point of View

Analysis and interpretability of machine learning models to classify thyroid disease

Overview of the TREC 2019 Precision Medicine Track.

Prediction of 30-day mortality in heart failure patients with hypoxic hepatitis: Development and external validation of an interpretable machine learning model

Modeling the Arden Syntax for medical decisions in XML

Smart Chinese medicine for hypertension treatment with a deep learning model

GPTEval: A Survey on Assessments of ChatGPT and GPT-4

Utilizing standardized nursing terminologies in implementing an AI-powered fall-prevention tool to improve patient outcomes: a multihospital study

Characterizing the limitations of using diagnosis codes in the context of machine learning for healthcare

A survey on detecting mental disorders with natural language processing: Literature review, trends and challenges

Generation of realistic synthetic data using Multimodal Neural Ordinary Differential Equations

FedNER: Medical Named Entity Recognition with Federated Learning