AIMC Topic: Risk Assessment
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Machine learning-based prediction of mortality risk in AIDS patients with comorbid common AIDS-related diseases or symptoms.
Frontiers in public health
Mar 12, 2025
OBJECTIVE: Early assessment and intervention of Acquired Immune Deficiency Syndrome (AIDS) patients at high risk of mortality is critical. This study aims to develop an optimally performing mortality risk prediction model for AIDS patients with comor...
Development of a visualized risk prediction system for sarcopenia in older adults using machine learning: a cohort study based on CHARLS.
Frontiers in public health
Mar 12, 2025
INTRODUCTION: The older adult are at high risk of sarcopenia, making early identification and scientific intervention crucial for healthy aging.
Use and Usefulness of Risk Prediction Tools in Urologic Surgery: Current State and Path Forward.
Urology practice
Mar 11, 2025
INTRODUCTION: Although the enthusiasm for artificial intelligence (AI) to enhance surgical decision-making continues to grow, the preceding advance of risk prediction tools (RPTs) has had limited impact to date. To help inform the development of AI-p...
Contrast-Induced Acute Kidney Injury in Lower Limb Percutaneous Transluminal Angioplasty: A Machine Learning Approach for Preoperative Risk Prediction.
Annals of vascular surgery
Mar 11, 2025
BACKGROUND: Contrast-induced acute kidney injury (CI-AKI) is a common complication of lower limb percutaneous transluminal angioplasty (PTA). Common risk models are based on cardiology cohorts for percutaneous coronary intervention. They include a mi...
Predictive Value of Tests
Angioplasty
Glomerular Filtration Rate
Contrast Media
Lower Extremity
Peripheral Arterial Disease
Male
Middle Aged
Risk Assessment
Treatment Outcome
Acute Kidney Injury
Female
Humans
Reproducibility of Results
Machine Learning
Risk Factors
Decision Support Techniques
Aged
Retrospective Studies
Identifying individuals at risk for weight gain using machine learning in electronic medical records from the United States.
Diabetes, obesity & metabolism
Mar 11, 2025
AIMS: Numerous risk factors for the development of obesity have been identified, yet the aetiology is not well understood. Traditional statistical methods for analysing observational data are limited by the volume and characteristics of large dataset...
PrOsteoporosis: predicting osteoporosis risk using NHANES data and machine learning approach.
BMC research notes
Mar 11, 2025
OBJECTIVES: Osteoporosis, prevalent among the elderly population, is primarily diagnosed through bone mineral density (BMD) testing, which has limitations in early detection. This study aims to develop and validate a machine learning approach for ost...
Predicting periprosthetic joint infection in primary total knee arthroplasty: a machine learning model integrating preoperative and perioperative risk factors.
BMC musculoskeletal disorders
Mar 11, 2025
BACKGROUND: Periprosthetic joint infection leads to significant morbidity and mortality after total knee arthroplasty. Preoperative and perioperative risk prediction and assessment tools are lacking in Asia. This study developed the first machine lea...
Risk-based evaluation of machine learning-based classification methods used for medical devices.
BMC medical informatics and decision making
Mar 11, 2025
BACKGROUND: In the future, more medical devices will be based on machine learning (ML) methods. In general, the consideration of risks is a crucial aspect for evaluating medical devices. Accordingly, risks and their associated costs should be taken i...
Individual and integrated indexes of inflammation predicting the risks of mental disorders - statistical analysis and artificial neural network.
BMC psychiatry
Mar 11, 2025
OBJECTIVE: The prevalence of mental illness in Taiwan increased. Identifying and mitigating risk factors for mental illness is essential. Inflammation may be a risk factor for mental illness; however, the predictive power of inflammation test values ...
Development and validation of an interpretable machine learning model for predicting the risk of hepatocellular carcinoma in patients with chronic hepatitis B: a case-control study.
BMC gastroenterology
Mar 11, 2025
BACKGROUND: The aim of this study was to develop and internally validate an interpretable machine learning (ML) model for predicting the risk of hepatocellular carcinoma (HCC) in patients with chronic hepatitis B (CHB) infection.
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