AIMC Topic: ROC Curve

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Machine learning algorithms to predict the risk of hyperlipidemia in people with HIV after starting HAART for 6 months.

AIDS (London, England)
OBJECTIVE: The purpose of this study was to use machine learning models to predict the risk of hyperlipidemia in people with HIV (PWH) for 6 months after starting HAART, to improve early intervention efforts and prevent further progression to cardiov...

Nutritional and lifestyle predictors of rectal bleeding in functional constipation: A machine learning approach.

International journal of medical informatics
BACKGROUND: Rectal bleeding among young adults is an increasingly common clinical concern often linked with chronic constipation and unhealthy lifestyle habits. Early identification of at-risk individuals through machine learning models-based approac...

Predicting prolonged hospitalization in asthma patients: model development and external validation.

The Journal of asthma : official journal of the Association for the Care of Asthma
PURPOSE: This study aims to develop and validate a machine learning (ML) model to predict prolonged hospitalization in asthma patients.

Pseudotargeted metabolomics profiles potential damage-associated molecular patterns as machine learning predictors for acute pancreatitis.

Journal of pharmaceutical and biomedical analysis
Acute pancreatitis (AP) is a common gastrointestinal disease characterized by pancreatic cell damage and inflammation. Given the early clinical diagnosis and management challenges, exploring novel analytical frameworks from new orientations for inter...

Deep learning-based system for automatic identification of benign and malignant eyelid tumours.

The British journal of ophthalmology
AIMS: Our aim is to develop a deep learning-based system for automatically identifying and classifying benign and malignant tumours of the eyelid to improve diagnostic accuracy and efficiency.

Diagnostic Machine Learning Models of Infectious Mononucleosis in Children Based on Clinical Data: A Retrospective Multicenter Study.

Journal of medical virology
The clinical manifestations of infectious mononucleosis (IM) and acute respiratory tract infections (ARTI) exhibit significant similarities. We aim to develop cost-efficient models for IM in children utilizing the Shapley Additive explanation (SHAP) ...

Multiomics and Machine Learning Identify Immunometabolic Biomarkers for Active Tuberculosis Diagnosis Against Nontuberculous Mycobacteria and Latent Tuberculosis Infection.

Journal of proteome research
This study utilized multiomics combined with a comprehensive machine learning-based predictive modeling approach to identify, validate, and prioritize circulating immunometabolic biomarkers in distinguishing tuberculosis (TB) from nontuberculous myco...