AIMC Topic: Decision Support Techniques

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Machine-learning model for predicting left atrial thrombus in patients with paroxysmal atrial fibrillation.

BMC cardiovascular disorders Jun 2, 2025
OBJECTIVE: Left atrial thrombus (LAT) poses a significant risk for stroke and other thromboembolic complication in patients with atrial fibrillation (AF). This study aimed to evaluate the incidence and predictors of LAT in patients with paroxysmal AF...
Decision Support Techniques Prognosis Retrospective Studies Female Risk Factors Humans Machine Learning Incidence Predictive Value of Tests Thrombosis Atrial Fibrillation Heart Diseases Aged Male Middle Aged Risk Assessment China
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Comparison of machine learning models with conventional statistical methods for prediction of percutaneous coronary intervention outcomes: a systematic review and meta-analysis.

BMC cardiovascular disorders Apr 23, 2025
INTRODUCTION: Percutaneous coronary intervention (PCI) has been the main treatment of coronary artery disease (CAD). In this review, we aimed to compare the performance of machine learning (ML) vs. logistic regression (LR) models in predicting differ...
Risk Assessment Time Factors Treatment Outcome Predictive Value of Tests Reproducibility of Results Percutaneous Coronary Intervention Coronary Artery Disease Humans Risk Factors Aged Machine Learning Male Decision Support Techniques Middle Aged Female
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Estimated glucose disposal rate outperforms other insulin resistance surrogates in predicting incident cardiovascular diseases in cardiovascular-kidney-metabolic syndrome stages 0-3 and the development of a machine learning prediction model: a nationwide prospective cohort study.

Cardiovascular diabetology Apr 16, 2025
BACKGROUND: The American Heart Association recently introduced the concept of cardiovascular-kidney-metabolic (CKM) syndrome, highlighting the increasing importance of the complex interplay between metabolic, renal, and cardiovascular diseases (CVD)....
Blood Glucose Incidence Time Factors Insulin Resistance Longitudinal Studies Metabolic Syndrome Kidney Diseases Predictive Value of Tests Male Cardiovascular Diseases Middle Aged Risk Assessment China Biomarkers Prognosis Female Risk Factors Aged Humans Machine Learning Decision Support Techniques Prospective Studies
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Using fuzzy decision support to create a positive mental health environment for preschoolers.

Scientific reports Apr 10, 2025
The preschool period is a crucial time for behavioural and social-emotional development and the cultivation of mental well-being. Preschoolers may be affected by various traumatic problems. During this process, preschoolers may develop hazardous beha...
Child Behavior Female Mental Health Male Child, Preschool Fuzzy Logic Humans Decision Support Techniques
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Evaluation of machine learning methods for prediction of heart failure mortality and readmission: meta-analysis.

BMC cardiovascular disorders Apr 7, 2025
BACKGROUND: Heart failure (HF) impacts nearly 6 million individuals in the U.S., with a projected 46% increase by 2030, is creating significant healthcare burdens. Predictive models, particularly machine learning (ML)-based models, offer promising so...
Humans Machine Learning Decision Support Techniques Prognosis Risk Assessment Predictive Value of Tests Heart Failure Patient Readmission Female Reproducibility of Results Risk Factors Aged Male
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AI as a decision support tool in forensic image analysis: A pilot study on integrating large language models into crime scene investigation workflows.

Journal of forensic sciences Apr 4, 2025
This study evaluates the effectiveness of artificial intelligence (AI) tools (ChatGPT-4, Claude, and Gemini) in forensic image analysis of crime scenes, marking a significant step toward developing bespoke AI models for forensic applications. The res...
Humans Forensic Sciences Large Language Models Artificial Intelligence Decision Support Techniques Pilot Projects Image Processing, Computer-Assisted Workflow
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Improved prediction and risk stratification of major adverse cardiovascular events using an explainable machine learning approach combining plasma biomarkers and traditional risk factors.

Cardiovascular diabetology Apr 2, 2025
BACKGROUND: Cardiovascular diseases (CVD) remain the leading cause of morbidity and mortality globally. Traditional risk models, primarily based on established risk factors, often lack the precision needed to accurately predict new-onset major advers...
Predictive Value of Tests Heart Disease Risk Factors United Kingdom Biomarkers Humans Cardiovascular Diseases Machine Learning Middle Aged Decision Support Techniques Risk Assessment Time Factors Metabolomics Prognosis Female Aged Male
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Machine Learning Models predicting Decompensation in Cirrhosis.

Journal of gastrointestinal and liver diseases : JGLD Mar 27, 2025
BACKGROUND AND AIMS: Decompensation of cirrhosis significantly decreases survival, thus, prevention of complications is paramount. We used machine learning techniques to identify parameters predicting decompensation.
Aged Male Humans Support Vector Machine Biomarkers Machine Learning Middle Aged Predictive Value of Tests Risk Assessment Decision Support Techniques Prognosis Bilirubin Liver Cirrhosis Retrospective Studies Databases, Factual Proof of Concept Study Female Prospective Studies Risk Factors
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Construction and validation of a predictive model for intracardiac thrombus risk in patients with dilated cardiomyopathy: a retrospective study.

BMC cardiovascular disorders Mar 27, 2025
BACKGROUND: Systemic embolic events due to exfoliation of intracardiac thrombus (ICT) are one of the catastrophic complications of dilated cardiomyopathy (DCM). This study intended to develop a prediction model to predict the risk of ICT in patients ...
Risk Factors Aged Adult Male Humans Middle Aged Cardiomyopathy, Dilated Risk Assessment Decision Support Techniques Support Vector Machine Prognosis Predictive Value of Tests Retrospective Studies Thrombosis Female Heart Diseases Reproducibility of Results
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Machine Learning Identification of Patient Phenoclusters in Aortic Regurgitation.

JACC. Cardiovascular imaging Mar 26, 2025
BACKGROUND: Current treatment paradigms assume aortic regurgitation (AR) patients to be a homogenous population, but varied courses of disease progression and outcomes are observed clinically.
Risk Assessment Disease Progression Severity of Illness Index Time Factors United States Aged Aortic Valve Magnetic Resonance Imaging, Cine Adult Humans Unsupervised Machine Learning Prognosis Male Machine Learning Predictive Value of Tests Retrospective Studies Ventricular Function, Left Decision Support Techniques Sex Factors Female Middle Aged Phenotype Aortic Valve Insufficiency Reproducibility of Results Risk Factors
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