AIMC Topic: Risk Assessment
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Machine Learning Multimodal Model for Delirium Risk Stratification.
JAMA network open
May 1, 2025
IMPORTANCE: Automating the identification of risk for developing hospital delirium with models that use machine learning (ML) could facilitate more rapid prevention, identification, and treatment of delirium. However, there are very few reports on th...
Multimodal Visualization and Explainable Machine Learning-Driven Markers Enable Early Identification and Prognosis Prediction for Symptomatic Aortic Stenosis and Heart Failure With Preserved Ejection Fraction After Transcatheter Aortic Valve Replacement: Multicenter Cohort Study.
Journal of medical Internet research
May 1, 2025
BACKGROUND: Currently, there is a paucity of literature addressing personalized risk stratification using multimodal data in patients with symptomatic aortic stenosis and heart failure with preserved ejection fraction (HFpEF) following transcatheter ...
Development and validation of a machine learning-based risk model for metastatic disease in nmCRPC patients: a tumor marker prognostic study.
International journal of surgery (London, England)
May 1, 2025
BACKGROUND: Nonmetastatic castration-resistant prostate cancer (nmCRPC) is a clinical challenge due to the high progression rate to metastasis and mortality. To date, no prognostic model has been developed to predict the metastatic probability for nm...
Unveiling PFAS hazard in European surface waters using an interpretable machine-learning model.
Environment international
Apr 30, 2025
Per- and polyfluoroalkyl substances (PFAS), commonly known as "forever chemicals", are ubiquitous in surface waters and potentially threaten human health and ecosystems. Despite extensive monitoring efforts, PFAS risk in European surface waters remai...
Using machine learning involving diagnoses and medications as a risk prediction tool for post-acute sequelae of COVID-19 (PASC) in primary care.
BMC medicine
Apr 30, 2025
BACKGROUND: The aim of our study was to determine whether the application of machine learning could predict PASC by using diagnoses from primary care and prescribed medication 1 year prior to PASC diagnosis.
Machine learning-based prediction of postoperative pancreatic fistula after laparoscopic pancreaticoduodenectomy.
BMC surgery
Apr 30, 2025
BACKGROUND: Clinically relevant postoperative pancreatic fistula (CR-POPF) following laparoscopic pancreaticoduodenectomy (LPD) is a critical complication that significantly worsens patient outcomes. However, the heterogeneity of its risk factors and...
Intelligent predictive risk assessment and management of sarcopenia in chronic disease patients using machine learning and a web-based tool.
European journal of medical research
Apr 29, 2025
BACKGROUND: Individuals with chronic diseases are at higher risk of sarcopenia, and precise prediction is essential for its prevention. This study aims to develop a risk scoring model using longitudinal data to predict the probability of sarcopenia i...
A deep-learning algorithm using real-time collected intraoperative vital sign signals for predicting acute kidney injury after major non-cardiac surgeries: A modelling study.
PLoS medicine
Apr 29, 2025
BACKGROUND: Postoperative acute kidney injury (PO-AKI) prediction models for non-cardiac major surgeries typically rely solely on preoperative clinical characteristics.
Suicide risk prediction for Korean adolescents based on machine learning.
Scientific reports
Apr 28, 2025
Traditional clinical risk assessment tools proved inadequate for reliably identifying individuals at high risk for suicidal behavior. As a result, machine learning (ML) techniques have become progressively incorporated into psychiatric care. This stu...
ExpoPath: A method for identifying and annotating exposure pathways from chemical co-occurrence networks.
The Science of the total environment
Apr 27, 2025
Improving risk evaluation for environmental and human health is of paramount concern for the U.S. Environmental Protection Agency (EPA). This includes the identification and assessment of chemical transport from commercial and industrial sources to e...
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