AIMC Topic: Decision Support Techniques

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Relationship between atherogenic index of plasma and length of stay in critically ill patients with atherosclerotic cardiovascular disease: a retrospective cohort study and predictive modeling based on machine learning.

Cardiovascular diabetology Feb 28, 2025
BACKGROUND: The atherogenic index of plasma (AIP) is considered an important marker of atherosclerosis and cardiovascular risk. However, its potential role in predicting length of stay (LOS), especially in patients with atherosclerotic cardiovascular...
Humans Machine Learning Decision Support Techniques Databases, Factual Biomarkers Prognosis Time Factors Predictive Value of Tests Atherosclerosis Aged Cholesterol, HDL Male Triglycerides Middle Aged Retrospective Studies Risk Assessment Critical Illness Length of Stay Intensive Care Units Female Risk Factors
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Optimized machine learning framework for cardiovascular disease diagnosis: a novel ethical perspective.

BMC cardiovascular disorders Feb 20, 2025
Alignment of advanced cutting-edge technologies such as Artificial Intelligence (AI) has emerged as a significant driving force to achieve greater precision and timeliness in identifying cardiovascular diseases (CVDs). However, it is difficult to ach...
Diagnosis, Computer-Assisted Decision Trees Predictive Value of Tests Humans Machine Learning Decision Support Techniques Reproducibility of Results Cardiovascular Diseases
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Stress hyperglycemia ratio and machine learning model for prediction of all-cause mortality in patients undergoing cardiac surgery.

Cardiovascular diabetology Feb 15, 2025
BACKGROUND: The stress hyperglycemia ratio (SHR) was developed to reduce the effects of long-term chronic glycemic factors on stress hyperglycemia levels, which was associated with adverse clinical outcomes. This study aims to evaluate the relationsh...
Treatment Outcome Predictive Value of Tests Cause of Death Cardiac Surgical Procedures Stress, Physiological Female Risk Factors Aged Male Middle Aged Risk Assessment Blood Glucose Time Factors Hospital Mortality Hyperglycemia Machine Learning Decision Support Techniques Databases, Factual Biomarkers Retrospective Studies Humans
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Predicting major adverse cardiac events in diabetes and chronic kidney disease: a machine learning study from the Silesia Diabetes-Heart Project.

Cardiovascular diabetology Feb 15, 2025
BACKGROUND: People living with diabetes mellitus (DM) and chronic kidney disease (CKD) are at significantly high risk of cardiovascular events (CVEs), however the predictive performance of traditional risk prediction methods are limited.
Humans Machine Learning Decision Support Techniques Databases, Factual Prognosis Incidence Time Factors Renal Insufficiency, Chronic Diabetes Mellitus Predictive Value of Tests Female Aged Male Middle Aged Risk Assessment Heart Disease Risk Factors
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Predicting cardiovascular outcomes in Chinese patients with type 2 diabetes by combining risk factor trajectories and machine learning algorithm: a cohort study.

Cardiovascular diabetology Feb 7, 2025
BACKGROUND: Cardiovascular complications are major concerns for Chinese patients with type 2 diabetes. Accurately predicting these risks remains challenging due to limitations in traditional risk models. We aimed to develop a dynamic prediction model...
Cardiovascular Diseases Middle Aged Risk Assessment China Time Factors Diabetes Mellitus, Type 2 East Asian People Predictive Value of Tests Prognosis Heart Disease Risk Factors Humans Female Machine Learning Reproducibility of Results Decision Support Techniques Aged Male
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Prediction of obstructive coronary artery disease using coronary calcification and epicardial adipose tissue assessments from CT calcium scoring scans.

Journal of cardiovascular computed tomography Feb 4, 2025
BACKGROUND: Low-cost/no-cost non-contrast CT calcium scoring (CTCS) exams can provide direct evidence of coronary atherosclerosis. In this study, using features from CTCS images, we developed a novel machine learning model to predict obstructive coro...
Risk Factors Humans Aged Coronary Vessels Machine Learning Male Vascular Calcification Decision Support Techniques Middle Aged Computed Tomography Angiography Prognosis Risk Assessment Pericardium Female Severity of Illness Index Epicardial Adipose Tissue Reproducibility of Results Adipose Tissue Predictive Value of Tests Coronary Angiography Coronary Artery Disease
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Prognosis modelling of adverse events for post-PCI treated AMI patients based on inflammation and nutrition indexes.

BMC cardiovascular disorders Jan 23, 2025
OBJECTIVE: This study aimed to evaluate the predictive performance of inflammatory and nutritional indices for adverse cardiovascular events (ACE) in patients with acute myocardial infarction (AMI) after percutaneous coronary intervention (PCI) using...
Middle Aged Nutritional Status Nutrition Assessment Risk Assessment Inflammation Humans Biomarkers Treatment Outcome Decision Trees Neural Networks, Computer Female Machine Learning Risk Factors Predictive Value of Tests Decision Support Techniques Aged Percutaneous Coronary Intervention Male Myocardial Infarction Inflammation Mediators
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Early Prediction of Cardio Vascular Disease (CVD) from Diabetic Retinopathy using improvised deep Belief Network (I-DBN) with Optimum feature selection technique.

BMC cardiovascular disorders Jan 18, 2025
Cardio Vascular Disease (CVD) is one of the leading causes of mortality and it is estimated that 1 in 4 deaths happens due to it. The disease prevalence rate becomes higher since there is an inadequate system/model for predicting CVD at an earliest. ...
Prognosis Female Humans Cardiovascular Diseases Early Diagnosis Reproducibility of Results Diabetic Retinopathy Middle Aged Risk Factors Decision Support Techniques Male Risk Assessment Deep Learning Predictive Value of Tests
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Integrating intuitionistic fuzzy and MCDM methods for sustainable energy management in smart factories.

PloS one Jan 14, 2025
Improving energy efficiency is crucial for smart factories that want to meet sustainability goals and operational excellence. This study introduces a novel decision-making framework to optimize energy efficiency in smart manufacturing environments, i...
Renewable Energy Decision Support Techniques Fuzzy Logic Decision Making Conservation of Energy Resources
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Developing a decision support tool to predict delayed discharge from hospitals using machine learning.

BMC health services research Jan 11, 2025
BACKGROUND: The growing demand for healthcare services challenges patient flow management in health systems. Alternative Level of Care (ALC) patients who no longer need acute care yet face discharge barriers contribute to prolonged stays and hospital...
Middle Aged Length of Stay Decision Support Techniques Patient Discharge Nova Scotia Humans Female Aged Neural Networks, Computer Adult Machine Learning Male
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