AIMC Topic: ROC Curve

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Automated Deep Learning Phenotyping of Tricuspid Regurgitation in Echocardiography.

JAMA cardiology Jun 1, 2025
IMPORTANCE: Accurate assessment of tricuspid regurgitation (TR) is necessary for identification and risk stratification.
Humans Phenotype Female Deep Learning ROC Curve Tricuspid Valve Insufficiency Echocardiography, Doppler, Color Aged Male Middle Aged Severity of Illness Index
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Temporal validation of machine learning models for pre-eclampsia prediction using routinely collected maternal characteristics: A validation study.

Computers in biology and medicine Jun 1, 2025
BACKGROUND: Pre-eclampsia (PE) contributes to more than one-fourth of all maternal deaths and half a million newborn deaths worldwide every year. Early screening and interventions can reduce PE incidence and related complications. We aim to 1) tempor...
Logistic Models Australia Pre-Eclampsia Pregnancy Humans Female Machine Learning Adult ROC Curve
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Fusion of multi-scale feature extraction and adaptive multi-channel graph neural network for 12-lead ECG classification.

Computer methods and programs in biomedicine Jun 1, 2025
BACKGROUND AND OBJECTIVE: The 12-lead electrocardiography (ECG) is a widely used diagnostic method in clinical practice for cardiovascular diseases. The potential correlation between interlead signals is an important reference for clinical diagnosis ...
Graph Neural Networks Deep Learning Humans ROC Curve Electrocardiography Neural Networks, Computer Signal Processing, Computer-Assisted Algorithms Cardiovascular Diseases
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Evaluating the National Early Warning Score (NEWS) in triage: A machine learning perspective.

International emergency nursing Jun 1, 2025
BACKGROUND: The National Early Warning Score is widely used in Emergency Departments for triage, primarily to predict mortality. However, its effectiveness in assessing additional clinical outcomes relevant to triage, such as patient urgency and seve...
Early Warning Score ROC Curve Triage Emergency Service, Hospital Prospective Studies Intensive Care Units Female Humans Machine Learning Aged Adult Male Middle Aged
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Optimizing stability of heart disease prediction across imbalanced learning with interpretable Grow Network.

Computer methods and programs in biomedicine Jun 1, 2025
BACKGROUND AND OBJECTIVES: Heart disease prediction models often face stability challenges when applied to public datasets due to significant class imbalances, unlike the more balanced benchmark datasets. These imbalances can adversely affect various...
Humans Neural Networks, Computer Machine Learning Algorithms Risk Factors Heart Diseases ROC Curve
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Chat-GPT in triage: Still far from surpassing human expertise - An observational study.

The American journal of emergency medicine Jun 1, 2025
BACKGROUND: Triage is essential in emergency departments (EDs) to prioritize patient care based on clinical urgency. Recent investigations have explored the role of large language models (LLMs) in triage, but their effectiveness compared to human tri...
Sensitivity and Specificity Female Humans ROC Curve Reproducibility of Results Artificial Intelligence Male Generative Artificial Intelligence Aged Middle Aged Retrospective Studies Triage Adult Emergency Service, Hospital
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Pediatric Electrocardiogram-Based Deep Learning to Predict Secundum Atrial Septal Defects.

Pediatric cardiology Jun 1, 2025
Secundum atrial septal defect (ASD2) detection is often delayed, with the potential for late diagnosis complications. Recent work demonstrated artificial intelligence-enhanced ECG analysis shows promise to detect ASD2 in adults. However, its applicat...
Male Humans ROC Curve Adolescent Retrospective Studies Child, Preschool Echocardiography Electrocardiography Child Female Infant Heart Septal Defects, Atrial Deep Learning
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Automated diagnosis for extraction difficulty of maxillary and mandibular third molars and post-extraction complications using deep learning.

Scientific reports May 30, 2025
Optimal surgical methods require accurate prediction of extraction difficulty and complications. Although various automated methods related to third molar (M3) extraction have been proposed, none fully predict both extraction difficulty and post-extr...
Mandible Radiography, Panoramic Tooth Extraction Maxilla Deep Learning ROC Curve Molar, Third Humans Female Adult Male Postoperative Complications
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Predicting thyroid cancer recurrence using supervised CatBoost: A SHAP-based explainable AI approach.

Medicine May 30, 2025
Recurrence prediction in well-differentiated thyroid cancer remains a clinical challenge, necessitating more accurate and interpretable predictive models. This study investigates the use of a supervised CatBoost classifier to predict recurrence in we...
Supervised Machine Learning Boosting Machine Learning Algorithms Thyroid Neoplasms ROC Curve Neoplasm Recurrence, Local Humans Female Aged Adult Male Middle Aged Risk Assessment
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Comparison of machine learning models for predicting stroke risk in hypertensive patients: Lasso regression model, random forest model, Boruta algorithm model, and Boruta algorithm combined with Lasso regression model.

Medicine May 30, 2025
The aim of this study was to compare the performance of 4 machine learning models-Lasso regression model, random forest model, Boruta algorithm model, and the Boruta algorithm combined with Lasso regression-in predicting stroke risk among hypertensiv...
Humans Machine Learning Male Middle Aged Risk Assessment ROC Curve Algorithms Female Risk Factors Aged Random Forest Stroke Hypertension Regression Analysis Area Under Curve
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