AIMC Topic: Cardiovascular Diseases
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Artificial Intelligence-Derived Risk Prediction: A Novel Risk Calculator Using Office and Ambulatory Blood Pressure.
Hypertension (Dallas, Tex. : 1979)
Apr 25, 2024
BACKGROUND: Quantification of total cardiovascular risk is essential for individualizing hypertension treatment. This study aimed to develop and validate a novel, machine-learning-derived model to predict cardiovascular mortality risk using office bl...
An efficient cardio vascular disease prediction using multi-scale weighted feature fusion-based convolutional neural network with residual gated recurrent unit.
Computer methods in biomechanics and biomedical engineering
Apr 17, 2024
The cardiovascular disease (CVD) is the dangerous disease in the world. Most of the people around the world are affected by this dangerous CVD. In under-developed countries, the prediction of CVD remains the toughest job and it takes more time and co...
Enhanced Cardiovascular Disease Prediction Modelling using Machine Learning Techniques: A Focus on CardioVitalnet.
Network (Bristol, England)
Apr 16, 2024
Aiming at early detection and accurate prediction of cardiovascular disease (CVD) to reduce mortality rates, this study focuses on the development of an intelligent predictive system to identify individuals at risk of CVD. The primary objective of th...
Prediction of cardiovascular risk factors from retinal fundus photographs: Validation of a deep learning algorithm in a prospective non-interventional study in Kenya.
Diabetes, obesity & metabolism
Apr 15, 2024
AIM: Hypertension and diabetes mellitus (DM) are major causes of morbidity and mortality, with growing burdens in low-income countries where they are underdiagnosed and undertreated. Advances in machine learning may provide opportunities to enhance d...
Advanced cardiac imaging, machine learning, and heart age for cardiovascular risk stratification.
The international journal of cardiovascular imaging
Apr 13, 2024
Cardiovascular disease risk assessment through sensing the circulating microbiome with perovskite quantum dots leveraging deep learning models for bacterial species selection.
Mikrochimica acta
Apr 10, 2024
Perovskite quantum dots (PQDs) are novel nanomaterials wherein perovskites are used to formulate quantum dots (QDs). The present study utilizes the excellent fluorescence quantum yields of these nanomaterials to detect 16S rRNA of circulating microbi...
Artificial Intelligence for Cardiovascular Care-Part 1: Advances: JACC Review Topic of the Week.
Journal of the American College of Cardiology
Apr 7, 2024
Recent artificial intelligence (AI) advancements in cardiovascular care offer potential enhancements in diagnosis, treatment, and outcomes. Innovations to date focus on automating measurements, enhancing image quality, and detecting diseases using no...
Artificial Intelligence in Cardiovascular Care-Part 2: Applications: JACC Review Topic of the Week.
Journal of the American College of Cardiology
Apr 7, 2024
Recent artificial intelligence (AI) advancements in cardiovascular care offer potential enhancements in effective diagnosis, treatment, and outcomes. More than 600 U.S. Food and Drug Administration-approved clinical AI algorithms now exist, with 10% ...
Prediction of adverse cardiovascular events in children using artificial intelligence-based electrocardiogram.
International journal of cardiology
Apr 3, 2024
BACKGROUND: Convolutional neural networks (CNNs) have emerged as a novel method for evaluating heart failure (HF) in adult electrocardiograms (ECGs). However, such CNNs are not applicable to pediatric HF, where abnormal anatomy of congenital heart de...
Deep Learning to Estimate Cardiovascular Risk From Chest Radiographs : A Risk Prediction Study.
Annals of internal medicine
Mar 26, 2024
BACKGROUND: Guidelines for primary prevention of atherosclerotic cardiovascular disease (ASCVD) recommend a risk calculator (ASCVD risk score) to estimate 10-year risk for major adverse cardiovascular events (MACE). Because the necessary inputs are o...
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