AIMC Topic: Risk Factors

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The risk factors for relapse behavior in individuals with substance use disorders: An interpretable machine learning study.

Journal of affective disorders
BACKGROUND: Substance abuse has become a serious public health problem worldwide, and finding effective prevention and treatment strategies is undoubtedly an urgent need. This study addresses the risk factors that lead to relapse behaviors among subs...

Enhanced Detection, Using Deep Learning Technology, of Medial Meniscal Posterior Horn Ramp Lesions in Patients with ACL Injury.

The Journal of bone and joint surgery. American volume
BACKGROUND: Meniscal ramp lesions can impact knee stability, particularly when associated with anterior cruciate ligament (ACL) injuries. Although magnetic resonance imaging (MRI) is the primary diagnostic tool, its diagnostic accuracy remains subopt...

Machine learning-based predictive modeling of depressive symptoms in Chinese adolescents.

Journal of affective disorders
BACKGROUND: The aim is to develop prediction models by lifestyles indicators as well as socioeconomic status to predict the risk of depressive symptoms in adolescents, and to rank and explain these predictors.

`Probabilistic ensemble learning for prediction of stroke thrombectomy outcomes from the NeuroVascular Quality Initiative-Quality Outcomes Database (NVQI-QOD) Acute Ischemic Stroke Registry.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
INTRODUCTION: Mechanical Thrombectomy (MT) is the standard of care in the interventional management of Acute Ischemic Stroke (AIS). The NVQI-QOD registry records detailed patient characteristics, pre-operative imaging, procedure metrics, and post-ope...

Prediabetes phenotypes: can aetiology and risk profile guide lifestyle strategies for diabetes prevention?

Expert review of endocrinology & metabolism
INTRODUCTION: Type 2 diabetes (T2D) continues to worsen globally alongside rise in obesity. Asymptomatic dysglycaemia, which precedes T2D, provides opportunities to identify those at risk and target prevention but prediabetes is highly variable. Not ...

Prediction model for postoperative urinary retention in patients undergoing totally extraperitoneal groin hernia repair.

Surgery
BACKGROUND: Postoperative urinary retention remains a common complication after totally extraperitoneal groin hernia repair, often prolonging hospitalization and increasing patient discomfort. This study aimed to develop a prediction model using mach...

Artificial intelligence and digital twins for the personalised prediction of hypertension risk.

Computers in biology and medicine
Hypertension is a significant global health challenge, contributing substantially to morbidity and mortality through its association with various cardiovascular diseases. Traditional approaches to hypertension risk prediction, which rely on broad epi...

Heterogeneity in the association between internet use and dementia among older adults: A machine-learning analysis.

Archives of gerontology and geriatrics
BACKGROUND & AIMS: Internet use among older adults may reduce the risk of dementia, but it remains unknown how the effects vary across individuals. The aim of this study was to rigorously examine heterogeneity in the association between internet use ...

Nutritional and lifestyle predictors of rectal bleeding in functional constipation: A machine learning approach.

International journal of medical informatics
BACKGROUND: Rectal bleeding among young adults is an increasingly common clinical concern often linked with chronic constipation and unhealthy lifestyle habits. Early identification of at-risk individuals through machine learning models-based approac...