AIMC Topic: Decision Support Techniques

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Evaluation of antiarrhythmia drug through QSPR modeling and multi criteria decision analysis.

Scientific reports Aug 9, 2025
This study explores how topological indices (TIs), which are mathematical descriptors of a drug's molecular structure, can support to predict vital properties and biological activities. This understanding is a key for more effective drug design. We f...
Decision Support Techniques Models, Molecular Anti-Arrhythmia Agents Arrhythmias, Cardiac Quantitative Structure-Activity Relationship Humans
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Design and Validation of a Chatbot-Based Cervical Cancer Screening Decision Aid for Women Experiencing Socioeconomic Disadvantage: User-Centered Approach Study.

JMIR cancer Jul 24, 2025
BACKGROUND: Cervical cancer (CC) screening participation remains suboptimal among vulnerable populations in France. This study aimed to develop and evaluate AppDate-You, a chatbot-based decision aid, to support women from socioeconomically disadvanta...
Humans Decision Support Techniques Generative Artificial Intelligence Socioeconomic Factors Female Aged Adult Uterine Cervical Neoplasms Socioeconomic Disparities in Health Middle Aged Vulnerable Populations Qualitative Research Mobile Applications Papillomavirus Infections Early Detection of Cancer France Focus Groups
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The Impact of Machine Learning Mortality Risk Prediction on Clinician Prognostic Accuracy and Decision Support: A Randomized Vignette Study.

Medical decision making : an international journal of the Society for Medical Decision Making Jul 4, 2025
BackgroundMachine learning (ML) algorithms may improve the prognosis for serious illnesses such as cancer, identifying patients who may benefit from earlier palliative care (PC) or advance care planning (ACP). We evaluated the impact of various prese...
Prognosis Female Adult Male Middle Aged Risk Assessment Surveys and Questionnaires Lung Neoplasms Carcinoma, Non-Small-Cell Lung Advance Care Planning Humans Machine Learning Algorithms Decision Support Techniques
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Prediction of three-year all-cause mortality in patients with heart failure and atrial fibrillation using the CatBoost model.

BMC cardiovascular disorders Jul 4, 2025
BACKGROUND: Heart failure and atrial fibrillation (HF-AF) frequently coexist, resulting in complex interactions that substantially elevate mortality risk. This study aimed to develop and validate a machine learning (ML) model predicting the 3-year al...
Boosting Machine Learning Algorithms Predictive Value of Tests Retrospective Studies Cause of Death Humans Female Heart Failure Aged, 80 and over Machine Learning Reproducibility of Results Atrial Fibrillation Male Decision Support Techniques Risk Factors Prognosis Aged Middle Aged Risk Assessment Time Factors
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Predicting carotid atherosclerosis in latent autoimmune diabetes in adult patients using machine learning models: a retrospective study.

BMC cardiovascular disorders Jul 3, 2025
BACKGROUND: Latent autoimmune diabetes in adults (LADA) is a slowly progressing form of diabetes with autoimmune origins. Patients with LADA are at an elevated risk of developing cardiovascular diseases, including carotid atherosclerosis. While machi...
Retrospective Studies Female Risk Factors Aged Adult Humans Machine Learning Decision Support Techniques Prognosis Predictive Value of Tests Carotid Artery Diseases Latent Autoimmune Diabetes in Adults Cross-Sectional Studies Male Middle Aged Risk Assessment China
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Predicting mortality risk following major lower extremity amputation using machine learning.

Journal of vascular surgery Jun 4, 2025
OBJECTIVE: Major lower extremity amputation for advanced vascular disease involves significant perioperative risks. Although outcome prediction tools could aid in clinical decision-making, they remain limited. To address this, we developed machine le...
Male Middle Aged Risk Assessment Postoperative Complications Time Factors Retrospective Studies Female Humans Risk Factors Machine Learning Aged Decision Support Techniques Aged, 80 and over Databases, Factual Treatment Outcome Lower Extremity Predictive Value of Tests Amputation, Surgical
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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 Humans Heart Diseases Female Machine Learning Risk Factors Aged Incidence Male Predictive Value of Tests Middle Aged Thrombosis Risk Assessment Atrial Fibrillation 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 Reproducibility of Results Coronary Artery Disease Humans Time Factors Risk Factors Machine Learning Treatment Outcome Aged Decision Support Techniques Predictive Value of Tests Male Female Percutaneous Coronary Intervention Middle Aged
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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)....
Aged Male Humans Cardiovascular Diseases Biomarkers Middle Aged China Machine Learning Longitudinal Studies Prognosis Blood Glucose Decision Support Techniques Risk Assessment Metabolic Syndrome Female Incidence Prospective Studies Kidney Diseases Risk Factors Time Factors Predictive Value of Tests Insulin Resistance
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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, Preschool Fuzzy Logic Child Behavior Decision Support Techniques Humans Female Mental Health Male
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