BACKGROUND: We aimed to develop and validate an Artificial Intelligence (AI) model that leverages CCTA and optical coherence tomography (OCT) images for automated analysis of plaque characteristics and coronary function.
OBJECTIVE: To resolve the underestimation problem and investigate the mechanism of the AI model which employed to predict cardiovascular disease (CVD) risk scores from retinal fundus photos.
Heart failure (HF) is marked by significant morbidity, mortality, and readmission rates, highlighting a critical need for accurate assessment of treatment efficacy. The New York Heart Association (NYHA) classification, while standard, falls short in ...
Cognitive impairment in cerebral small vessel disease (CSVD) progresses subtly but carries significant clinical consequences, necessitating effective diagnostic tools. This study developed and validated predictive models for CSVD-related cognitive im...
BACKGROUND: Thyroid nodules classified within the Thyroid Imaging Reporting and Data Systems (TI-RADS) category 3-5 are typically regarded as having varying degrees of malignancy risk, with the risk increasing from TI-RADS 3 to TI-RADS 5. While some ...
The journal of prevention of Alzheimer's disease
Mar 8, 2025
BACKGROUND: Integrating machine learning with medical records offers potential for early detection of Alzheimer's disease (AD), enabling timely interventions.
: Diet plays an important role in preventing and managing the progression from prediabetes to type 2 diabetes mellitus (T2DM). This study aims to develop prediction models incorporating specific dietary indicators and explore the performance in T2DM ...
International journal of molecular sciences
Mar 8, 2025
Mild cognitive impairment (MCI) is a clinical condition characterized by a decline in cognitive ability and progression of cognitive impairment. It is often considered a transitional stage between normal aging and Alzheimer's disease (AD). This study...
BACKGROUND: To evaluate the clinical applicability of deep learning (DL) models based on automatic segmentation in preoperatively predicting tumor spread through air spaces (STAS) in peripheral stage I lung adenocarcinoma (LUAD).
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