AIMC Topic: Risk Assessment
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Primary prevention cardiovascular disease risk prediction model for contemporary Chinese (1°P-CARDIAC): Model derivation and validation using a hybrid statistical and machine-learning approach.
PloS one
Jul 28, 2025
BACKGROUND: Cardiovascular disease (CVD) is the leading cause of mortality and morbidity in China and worldwide while we are lacking in validated primary prevention model specifically for Chinese. To identify CVD high-risk individuals for early inter...
Development and validation of machine learning-based risk prediction models for ICU-acquired weakness: a prospective cohort study.
European journal of medical research
Jul 24, 2025
BACKGROUND: Intensive care unit (ICU)-acquired weakness (ICUAW) is a prevalent complication in critically ill patients, marked by symmetrical respiratory and limb muscle weakness, which adversely affects long-term outcomes. Early identification of hi...
Optimized feature selection and advanced machine learning for stroke risk prediction in revascularized coronary artery disease patients.
BMC medical informatics and decision making
Jul 24, 2025
BACKGROUND: Coronary artery disease (CAD) remains a leading cause of global mortality, with stroke constituting a significant complication among patients undergoing coronary revascularization procedures, such as percutaneous coronary intervention (PC...
Predicting mortality risk in Alzheimer's disease using machine learning based on lifestyle and physical activity.
Scientific reports
Jul 24, 2025
Alzheimer's disease (AD), a progressive neurodegenerative disorder, significantly impacts patient survival, prompting the need for accurate prognostic tools. Lifestyle factors and physical activity levels have been identified as critical modifiable r...
Development and validation of risk prediction models for acute kidney disease in gout patients: a retrospective study using machine learning.
European journal of medical research
Jul 23, 2025
BACKGROUND: Limited research has been conducted on the prevalence of acute kidney injury (AKI) and acute kidney disease (AKD) in gout patients, as well as the impact of these renal complications on patient outcomes. This study aims to develop machine...
Early detection of ICU-acquired infections using high-frequency electronic health record data.
BMC medical informatics and decision making
Jul 21, 2025
BACKGROUND: Nosocomial infections are a major cause of morbidity and mortality in the ICU. Earlier identification of these complications may facilitate better clinical management and improve outcomes. We developed a dynamic prediction model that leve...
Development and performance of female breast cancer incidence risk prediction models: a systematic review and meta-analysis.
Annals of medicine
Jul 20, 2025
INTRODUCTION: Accurate breast cancer risk prediction is essential for early detection and personalized prevention strategies. While traditional models, such as Gail and Tyrer-Cuzick, are widely utilized, machine learning-based approaches may offer en...
Groundwater quality assessment and health risk evaluation for schoolchildren in Mujibnagar, Bangladesh: safe consumption guidelines using artificial neural network modeling.
Environmental geochemistry and health
Jul 20, 2025
Groundwater is a vital source of drinking water in Bangladesh, with tubewells commonly used, particularly in schools. This study assessed the quality of tubewell water in the southwest region, focusing on iron (Fe), arsenic (As), pH, electrical condu...
Collaborative assessment of the risk of postoperative progression in early-stage non-small cell lung cancer: a robust federated learning model.
Cancer imaging : the official publication of the International Cancer Imaging Society
Jul 18, 2025
BACKGROUND: While the TNM staging system provides valuable insights into the extent of disease, predicting postoperative progression in early-stage non-small cell lung cancer (NSCLC) remains a significant challenge. An effective bioimaging prognostic...
Comprehensive interaction modeling with machine learning improves prediction of disease risk in the UK Biobank.
Nature communications
Jul 18, 2025
Understanding how risk factors interact to jointly influence disease risk can provide insights into disease development and improve risk prediction. Here we introduce survivalFM, a machine learning extension to the widely used Cox proportional hazard...
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