AI Medical Compendium Topic:
ROC Curve

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AI-enhanced integration of genetic and medical imaging data for risk assessment of Type 2 diabetes.

Nature communications
Type 2 diabetes (T2D) presents a formidable global health challenge, highlighted by its escalating prevalence, underscoring the critical need for precision health strategies and early detection initiatives. Leveraging artificial intelligence, particu...

A multi-view fusion lightweight network for CRSwNPs prediction on CT images.

BMC medical imaging
Accurate preoperative differentiation of the chronic rhinosinusitis (CRS) endotype between eosinophilic CRS (eCRS) and non-eosinophilic CRS (non-eCRS) is an important topic in predicting postoperative outcomes and administering personalized treatment...

Development of interpretable machine learning models to predict in-hospital prognosis of acute heart failure patients.

ESC heart failure
AIMS: In recent years, there has been remarkable development in machine learning (ML) models, showing a trend towards high prediction performance. ML models with high prediction performance often become structurally complex and are frequently perceiv...

Identifying potential (re)hemorrhage among sporadic cerebral cavernous malformations using machine learning.

Scientific reports
The (re)hemorrhage in patients with sporadic cerebral cavernous malformations (CCM) was the primary aim for CCM management. However, accurately identifying the potential (re)hemorrhage among sporadic CCM patients in advance remains a challenge. This ...

Accuracy of artificial intelligence-assisted endoscopy in the diagnosis of gastric intestinal metaplasia: A systematic review and meta-analysis.

PloS one
BACKGROUND AND AIMS: Gastric intestinal metaplasia is a precancerous disease, and a timely diagnosis is essential to delay or halt cancer progression. Artificial intelligence (AI) has found widespread application in the field of disease diagnosis. Th...

Development of a machine learning-based model to predict prognosis of alpha-fetoprotein-positive hepatocellular carcinoma.

Journal of translational medicine
BACKGROUND: Patients with alpha-fetoprotein (AFP)-positive hepatocellular carcinoma (HCC) have aggressive biological behavior and poor prognosis. Therefore, survival time is one of the greatest concerns for patients with AFP-positive HCC. This study ...

Prediction of tuberculosis clusters in the riverine municipalities of the Brazilian Amazon with machine learning.

Revista brasileira de epidemiologia = Brazilian journal of epidemiology
OBJECTIVE: Tuberculosis (TB) is the second most deadly infectious disease globally, posing a significant burden in Brazil and its Amazonian region. This study focused on the "riverine municipalities" and hypothesizes the presence of TB clusters in th...

Machine Learning Quantification of Pulmonary Regurgitation Fraction from Echocardiography.

Pediatric cardiology
Assessment of pulmonary regurgitation (PR) guides treatment for patients with congenital heart disease. Quantitative assessment of PR fraction (PRF) by echocardiography is limited. Cardiac MRI (cMRI) is the reference-standard for PRF quantification. ...

Preoperative Differentiation of HER2-Zero and HER2-Low from HER2-Positive Invasive Ductal Breast Cancers Using BI-RADS MRI Features and Machine Learning Modeling.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Accurate determination of human epidermal growth factor receptor 2 (HER2) is important for choosing optimal HER2 targeting treatment strategies. HER2-low is currently considered HER2-negative, but patients may be eligible to receive new a...