Alle Papers – Machine Learning im Gesundheitswesen
104.164 Papers insgesamt · Seite 383 von 400
PortraitBooth: A Versatile Portrait Model for Fast Identity-Preserved Personalization
Adapting Text Embeddings for Causal Inference
Evaluating multivariate risk scores for clinical decision making.
Exploring ChatGPT’s Empathic Abilities
Design matters in patient-level prediction: evaluation of a cohort vs. case-control design when developing predictive models in observational healthcare datasets
Natural Language Processing of Clinical Documentation to Assess Functional Status in Patients With Heart Failure
Mitigating the risk of health inequity exacerbated by large language models
Addressing Data Scarcity in the Medical Domain: A GPT-Based Approach for Synthetic Data Generation and Feature Extraction
Development and validation of optimal phenomapping methods to estimate long-term atherosclerotic cardiovascular disease risk in patients with type 2 diabetes
Precision Medicine: Academic dreaming or clinical reality?
Explainable and programmable hypergraph convolutional network for imaging genetics data fusion
Optimization of Tree‐Based Machine Learning Models to Predict the Length of Hospital Stay Using Genetic Algorithm
Explainable Machine Learning Model for Chronic Kidney Disease Prediction
SPINE: SParse Interpretable Neural Embeddings
A survey on artificial intelligence techniques for chronic diseases: open issues and challenges
Prediction of Chronic Kidney Disease Using Machine Learning Technique
Use of Artificial Networks in Clinical Trials: A Pilot Study to Predict Responsiveness to Donepezil in Alzheimer's Disease
Artificial Intelligence
Clinical-Coder: Assigning Interpretable ICD-10 Codes to Chinese Clinical Notes
Text mining applied to electronic cardiovascular procedure reports to identify patients with trileaflet aortic stenosis and coronary artery disease
Implementation of Machine Learning Pipelines for Clinical Practice: Development and Validation Study
muhaz: Hazard Function Estimation in Survival Analysis
Cardiovascular Disease Prediction using Various Machine Learning Algorithms
BioGrid Australia facilitates collaborative medical and bioinformatics research across hospitals and medical research institutes by linking data from diverse disease and data types
Chatbots, Generative AI, and Scholarly Manuscripts