BACKGROUND: Identifying high risk factors and predicting lung cancer incidence risk are essential to prevention and intervention of lung cancer for the elderly. We aim to develop lung cancer incidence risk prediction model in the elderly to facilitat...
PURPOSE OF REVIEW: WHO defines SCD as sudden unexpected death either within 1 h of symptom onset (witnessed) or within 24 h of having been observed alive and symptom-free (unwitnessed). Sudden cardiac arrest is a major cause of mortality worldwide, w...
Predicting the outcome of a kidney transplant involving a living donor advances donor decision-making donors for clinicians and patients. However, the discriminative or calibration capacity of the currently employed models are limited. We set out to...
BACKGROUND: Accurate mortality prediction following transcatheter aortic valve implantation (TAVI) is essential for mitigating risk, shared decision-making and periprocedural planning. Surgical risk models have demonstrated modest discriminative valu...
INTRODUCTION: Propofol is a widely used sedative-hypnotic agent for critically ill patients requiring invasive mechanical ventilation (IMV). Despite its clinical benefits, propofol is associated with increased risks of hypertriglyceridemia. Early ide...
AIM: In this research, we leveraged bioinformatics and machine learning to pinpoint key risk genes associated with occupational benzene exposure and to construct genomic and algorithm-based predictive risk assessment models.
BACKGROUND: Multifaceted factors play a crucial role in the prevention and treatment of metabolic dysfunction-associated steatotic liver disease (MASLD). This study aimed to utilize multifaceted indicators to construct MASLD risk prediction machine l...
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Jan 20, 2025
This study introduces the Deep Learning-based Cardiovascular Disease Incident (DL-CVDi) score, a novel biomarker derived from routine abdominal CT scans, optimized to predict cardiovascular disease (CVD) risk using deep survival learning. CT imaging,...
STUDY OBJECTIVES: This study aimed to identify the risk factors associated with falls in hospitalized patients, develop a predictive risk model using machine learning algorithms, and evaluate the validity of the model's predictions.
Elderly patients undergoing maintenance hemodialysis (MHD) face a heightened risk of cognitive frailty (CF), which significantly compromises quality of life. Early identification of at-risk individuals and timely intervention are essential. Neverthel...