AIMC Topic: Risk Assessment

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Enhancing osteoporosis risk prediction using machine learning: A holistic approach integrating biomarkers and clinical data.

Computers in biology and medicine
Osteoporosis (OP) affects approximately 18 % of the global population, with osteoporosis-associated fractures impacting up to 37 million people annually. While dual-energy X-ray absorptiometry (DXA) remains the gold standard for diagnosis, its limita...

Automated machine learning model for predicting anastomotic strictures after esophageal cancer surgery: a retrospective cohort study.

Surgical endoscopy
BACKGROUND: Anastomotic strictures (AS) frequently occurs in patients following esophageal cancer surgery, significantly affecting their long-term quality of life. This study aims to develop a machine learning model to predict high-risk AS, enabling ...

Integrating Machine Learning and Dynamic Digital Follow-up for Enhanced Prediction of Postoperative Complications in Bariatric Surgery.

Obesity surgery
BACKGROUND: Traditional risk models, such as POSSUM and OS-MS, have limited accuracy in predicting complications after bariatric surgery. Machine learning (ML) offers new opportunities for personalized risk assessment by incorporating artificial inte...

AI-based prediction of left bundle branch block risk post-TAVI using pre-implantation clinical parameters.

Future cardiology
BACKGROUND AND AIMS: Transcatheter Aortic Valve Implantation (TAVI) has revolutionized the treatment of severe aortic stenosis. Although its clinical efficacy is well established, the development of new-onset left bundle branch block (LBBB) following...

Concise multi-class anxiety disorder risk assessment: A novel advanced machine learning approach.

Journal of anxiety disorders
Rapidly assessing anxiety disorder risk is crucial for effective mental health screen and intervention. However, traditional survey tools such as DASS-42 are time-consuming in responding and scoring. We used a novel advanced machine learning approach...

Refining source-specific lung cancer risk assessment from PM-bound PAHs: Integrating component-based potency factors and machine learning in Ningbo, China.

Ecotoxicology and environmental safety
The component-based potency factor approach, combined with benzo[a]pyrene (BaP) unit risk values from the World Health Organization (WHO), is commonly used to assess lung excess cancer risk (LECR) from polycyclic aromatic hydrocarbons (PAHs). However...

Visceral Fat Quantified by a Fully Automated Deep-Learning Algorithm and Risk of Incident and Recurrent Diverticulitis.

Diseases of the colon and rectum
BACKGROUND: Obesity is a risk factor for diverticulitis. However, it remains unclear whether visceral fat area, a more precise measurement of abdominal fat, is associated with the risk of diverticulitis.

Estimating individualized effectiveness of receiving successful recanalization for ischemic stroke cases using machine learning techniques.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
OBJECTIVES: Directly measuring the causal effect of mechanical thrombectomy (MT) for each ischemic stroke patient remains challenging, as it is impossible to observe the outcomes for both with and without successful recanalization in the same individ...

Exploring trade-offs in equitable stroke risk prediction with parity-constrained and race-free models.

Artificial intelligence in medicine
A recent analysis of common stroke risk prediction models showed that performance differs between Black and White subgroups, and that applying standard machine learning methods does not reduce these disparities. There have been calls in the clinical ...

Artificial Intelligence-Enabled Prediction of Heart Failure Risk From Single-Lead Electrocardiograms.

JAMA cardiology
IMPORTANCE: Despite the availability of disease-modifying therapies, scalable strategies for heart failure (HF) risk stratification remain elusive. Portable devices capable of recording single-lead electrocardiograms (ECGs) may enable large-scale com...