AIMC Topic: 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...
Comparison of cardiovascular risk prediction models developed using machine learning based on data from a Sri Lankan cohort with World Health Organization risk charts for predicting cardiovascular risk among Sri Lankans: a cohort study.
BMJ open
Jan 15, 2025
INTRODUCTION: Models derived from non-Sri Lankan cohorts are used for cardiovascular (CV) risk stratification of Sri Lankans.
Deep-learning prediction of cardiovascular outcomes from routine retinal images in individuals with type 2 diabetes.
Cardiovascular diabetology
Jan 2, 2025
BACKGROUND: Prior studies have demonstrated an association between retinal vascular features and cardiovascular disease (CVD), however most studies have only evaluated a few simple parameters at a time. Our aim was to determine whether a deep-learnin...
Humans
Diabetic Retinopathy
Decision Support Techniques
Risk Assessment
Deep Learning
Time Factors
Diabetes Mellitus, Type 2
Image Interpretation, Computer-Assisted
Photography
Retinal Vessels
Predictive Value of Tests
Heart Disease Risk Factors
Aged
Male
Cardiovascular Diseases
Middle Aged
Prognosis
Female
Reproducibility of Results
Risk Factors
Development and validation of a cardiovascular risk prediction model for Sri Lankans using machine learning.
PloS one
Oct 22, 2024
INTRODUCTION AND OBJECTIVES: Sri Lankans do not have a specific cardiovascular (CV) risk prediction model and therefore, World Health Organization(WHO) risk charts developed for the Southeast Asia Region are being used. We aimed to develop a CV risk ...
Image-based ECG analyzing deep-learning algorithm to predict biological age and mortality risks: interethnic validation.
Journal of cardiovascular medicine (Hagerstown, Md.)
Sep 12, 2024
BACKGROUND: Cardiovascular risk assessment is a critical component of healthcare, guiding preventive and therapeutic strategies. In this study, we developed and evaluated an image-based electrocardiogram (ECG) analyzing an artificial intelligence (AI...
Development of oculomics artificial intelligence for cardiovascular risk factors: A case study in fundus oculomics for HbA1c assessment and clinically relevant considerations for clinicians.
Asia-Pacific journal of ophthalmology (Philadelphia, Pa.)
Aug 28, 2024
Artificial Intelligence (AI) is transforming healthcare, notably in ophthalmology, where its ability to interpret images and data can significantly enhance disease diagnosis and patient care. Recent developments in oculomics, the integration of ophth...
Using machine learning-based algorithms to construct cardiovascular risk prediction models for Taiwanese adults based on traditional and novel risk factors.
BMC medical informatics and decision making
Jul 22, 2024
OBJECTIVE: To develop and validate machine learning models for predicting coronary artery disease (CAD) within a Taiwanese cohort, with an emphasis on identifying significant predictors and comparing the performance of various models.
Can Artificial Intelligence Change our Interpretation of Cardiovascular Risk Scores?
Arquivos brasileiros de cardiologia
Jul 19, 2024
A Systematic Review of Artificial Intelligence Models for Time-to-Event Outcome Applied in Cardiovascular Disease Risk Prediction.
Journal of medical systems
Jul 19, 2024
Artificial intelligence (AI) based predictive models for early detection of cardiovascular disease (CVD) risk are increasingly being utilised. However, AI based risk prediction models that account for right-censored data have been overlooked. This sy...
Digital twins: reimagining the future of cardiovascular risk prediction and personalised care.
Hellenic journal of cardiology : HJC = Hellenike kardiologike epitheorese
Jun 7, 2024
The rapid evolution of highly adaptable and reusable artificial intelligence models facilitates the implementation of digital twinning and has the potential to redefine cardiovascular risk prevention. Digital twinning combines vast amounts of data fr...
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