INTRODUCTION: Intensive care unit-acquired weakness (ICUAW) is a common and severe complication in critically ill patients, associated with high morbidity and poor prognosis. Despite increasing focus on ICUAW, definitive diagnostic and therapeutic st...
BACKGROUND: The development of sepsis in the intensive care unit (ICU) is rapid, the golden rescue time is short, and the effective way to reduce mortality is rapid diagnosis and early warning. Therefore, real-time prediction models play a key role i...
BACKGROUND: Conventional approaches for major depressive disorder (MDD) screening rely on two effective but subjective paradigms: self-rated scales and clinical interviews. Artificial intelligence (AI) can potentially contribute to psychiatry, especi...
Cancer stem cells (CSCs), distinguished by their abilities to differentiate and self-renew, play a pivotal role in the progression of colorectal cancer (CRC). However, the mechanisms that sustain CSCs in CRC remain unclear. This study aimed to identi...
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...
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...
Journal of health, population, and nutrition
May 29, 2025
BACKGROUND: Life's Essential 8 (LE8) for assessing cardiovascular health (CVH) has been demonstrated to be inversely associated with osteoporosis (OP). This study aims to create a machine learning (ML) model to assess the clinical association value o...
Machine learning technology has been extensively applied in the medical field, particularly in the context of disease prediction and patient rehabilitation assessment. Acute spinal cord injury (ASCI) is a sudden trauma that frequently results in seve...
This study aimed to determine whether trigeminal neuralgia can be diagnosed using convolutional neural networks (CNNs) based on plain X-ray skull images. A labeled dataset of 166 skull images from patients aged over 16 years with trigeminal neuralgia...
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