AIMC Topic: Risk Assessment

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AI Bias and Confounding Risk in Health Feature Engineering for Machine Learning Classification Task.

Studies in health technology and informatics
Recent advancements in machine learning bring unique opportunities in health fields but also pose considerable challenges. Due to stringent ethical considerations and resource constraints, health data can vary in scope, population coverage, and colle...

Developing risk stratification strategies and biomarkers for recurrent hepatocellular carcinoma.

Clinical and translational medicine
Hepatocellular carcinoma (HCC) remains a leading cause of cancer-related mortality, with high rates of post-resection recurrence posing significant clinical challenges. Early recurrence is largely driven by aggressive tumor biology, while late recurr...

Risk Stratification of Dengue Cases Requiring Hospitalization.

Journal of medical virology
Dengue pathogenesis involves immune-driven inflammation that contributes to severe disease progression. This study assessed a machine learning model to identify a minimal, yet highly predictive biomarker set, aiming to support clinical decision-makin...

Natural History of Cerebral Aneurysms: Risk Factors for Rupture and Implications for Management.

Neuroimaging clinics of North America
Intracranial aneurysms, affecting 2% to 3% of adults, present a significant health challenge due to their potential for sudden rupture, which entails high morbidity, mortality, and economic costs. Advances in computational neuroimaging, computational...

A model based on artificial intelligence for the prediction, prevention and patient-centred approach for non-communicable diseases related to metabolic syndrome.

European journal of public health
Metabolic syndrome (MetS) is related to non-communicable diseases (NCDs) such as type 2 diabetes (T2D), metabolic-associated steatotic liver disease (MASLD), atherogenic dyslipidaemia (ATD), and chronic kidney disease (CKD). The absence of reliable t...

Validation of the ACS-NSQIP surgical risk calculator for patients with paraoesophageal hernias undergoing robotic repair.

Surgical endoscopy
BACKGROUND: The National Surgical Quality Improvement Program (NSQIP) American College of Surgeons (ACS) risk calculator is a validated method of predicting postoperative complications that was recently updated to a machine-learning structure. The ob...

Emerging Technologies and Algorithms for Periodontal Screening and Risk of Disease Progression in Non-Dental Settings: A Scoping Review.

Journal of clinical periodontology
AIM: To evaluate different tools to screen for periodontal diseases and/or evaluate the risk for disease progression in non-dental clinical settings.

Interpretable Machine Learning Prediction Model for Predicting Mortality Risk of ICU Patients With Pressure Ulcers Based on the Braden Scale: A Clinical Study Based on MIMIC-IV.

Journal of clinical nursing
AIMS: This study was to create an interpretable machine learning model to predict the risk of mortality within 90 days for ICU patients suffering from pressure ulcers.

CLABpredICU---AI-driven risk prediction for CLABSI in intensive care units based on clinical and biochemical parameters.

American journal of infection control
BACKGROUND: Central line--associated bloodstream infections (CLABSI) are major causes of morbidity and mortality in intensive care units. This study aimed to develop an artificial intelligence-driven predictive model for CLABSI within 2 calendar days...

Associations of the Hs-CRP/HDL-C ratio with stroke among US adults: Evidence from NHANES 2015-2018.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
BACKGROUND: The high-sensitivity C-reactive protein (Hs-CRP)-to-high-density lipoprotein cholesterol (HDL-C) ratio, which integrates insights into inflammation and lipid metabolism, serves as a comprehensive indicator. The association between this ra...