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Risk Assessment

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Development, validation and economic evaluation of a machine learning algorithm for predicting the probability of kidney damage in patients with hyperuricaemia: protocol for a retrospective study.

BMJ open
INTRODUCTION: Accurate identification of the risk factors is essential for the effective prevention of hyperuricaemia (HUA)-related kidney damage. Previous studies have established the efficacy of machine learning (ML) methodologies in predicting kid...

Research on Risk Prediction of Condiments Based on Gray Correlation Analysis - Deep Neural Networks.

Journal of food protection
Food safety is directly related to the health of the public, and the safety of condiments is also of great significance. In this study, a risk assessment model for condiments based on gray correlation analysis was established by using publicly availa...

Screening for frequent hospitalization risk among community-dwelling older adult between 2016 and 2023: machine learning-driven item selection, scoring system development, and prospective validation.

Frontiers in public health
BACKGROUND: Screening for frequent hospitalizations in the community can help prevent super-utilizers from growing in the inpatient population. However, the determinants of frequent hospitalizations have not been systematically examined, their operat...

Machine-Learning-Based Predictive Model for Bothersome Stress Urinary Incontinence Among Parous Women in Southeastern China.

International urogynecology journal
INTRODUCTION AND HYPOTHESIS: Accurate identification of female populations at high risk for urinary incontinence (UI) and early intervention are potentially effective initiatives to reduce the prevalence of UI. We aimed to apply machine-learning tech...

Predictive Factors Driving Positive Awake Test in Carotid Endarterectomy Using Machine Learning.

Annals of vascular surgery
BACKGROUND: Positive neurologic awake testing during the carotid cross-clamping may be present in around 8% of patients undergoing carotid endarterectomy (CEA). The present work aimed to assess the accuracy of an artificial intelligence (AI)-powered ...

Identification of a Susceptible and High-Risk Population for Postoperative Systemic Inflammatory Response Syndrome in Older Adults: Machine Learning-Based Predictive Model.

Journal of medical Internet research
BACKGROUND: Systemic inflammatory response syndrome (SIRS) is a serious postoperative complication among older adult surgical patients that frequently develops into sepsis or even death. Notably, the incidences of SIRS and sepsis steadily increase wi...

Preferences for attributes of an artificial intelligence-based risk assessment tool for HIV and sexually transmitted infections: a discrete choice experiment.

BMC public health
INTRODUCTION: Early detection and treatment of HIV and sexually transmitted infections (STIs) are crucial for effective control. We previously developed MySTIRisk, an artificial intelligence-based risk tool that predicts the risk of HIV and STIs. We ...

Perioperative risk scores: prediction, pitfalls, and progress.

Current opinion in anaesthesiology
PURPOSE OF REVIEW: Perioperative risk scores aim to risk-stratify patients to guide their evaluation and management. Several scores are established in clinical practice, but often do not generalize well to new data and require ongoing updates to impr...