AIMC Topic: Cardiovascular Diseases
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Artificial intelligence in cardiology: a peek at the future and the role of ChatGPT in cardiology practice.
Journal of cardiovascular medicine (Hagerstown, Md.)
Sep 17, 2024
Artificial intelligence has increasingly become an integral part of our daily activities. ChatGPT, a natural language processing technology developed by OpenAI, is widely used in various industries, including healthcare. The application of ChatGPT in...
Development and validation of cardiometabolic risk predictive models based on LDL oxidation and candidate geromarkers from the MARK-AGE data.
Mechanisms of ageing and development
Sep 14, 2024
The predictive value of the susceptibility to oxidation of LDL particles (LDLox) in cardiometabolic risk assessment is incompletely understood. The main objective of the current study was to assess its relationship with other relevant biomarkers and ...
Application of AI-empowered scenario-based simulation teaching mode in cardiovascular disease education.
BMC medical education
Sep 13, 2024
BACKGROUND: Cardiovascular diseases present a significant challenge in clinical practice due to their sudden onset and rapid progression. The management of these conditions necessitates cardiologists to possess strong clinical reasoning and individua...
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...
Cardiovascular disease diagnosis: a holistic approach using the integration of machine learning and deep learning models.
European journal of medical research
Sep 11, 2024
BACKGROUND: The incidence and mortality rates of cardiovascular disease worldwide are a major concern in the healthcare industry. Precise prediction of cardiovascular disease is essential, and the use of machine learning and deep learning can aid in ...
Association of N-terminal pro-B natriuretic peptide with all-cause mortality and cardiovascular mortality in obese and non-obese populations and the development of a machine learning prediction model: National Health and Nutrition Examination Survey (NHANES) 1999-2004.
Diabetes, obesity & metabolism
Sep 6, 2024
AIMS: To explore the potential of N-terminal pro-B natriuretic peptide (NTproBNP) in identifying adverse outcomes, particularly cardiovascular adverse outcomes, in a population with obesity, and to establish a risk prediction model.
Mesocorticolimbic and Cardiometabolic Diseases-Two Faces of the Same Coin?
International journal of molecular sciences
Sep 6, 2024
The risk behaviors underlying the most prevalent chronic noncommunicable diseases (NCDs) encompass alcohol misuse, unhealthy diets, smoking and sedentary lifestyle behaviors. These are all linked to the altered function of the mesocorticolimbic (MCL)...
Trustworthy and ethical AI-enabled cardiovascular care: a rapid review.
BMC medical informatics and decision making
Sep 4, 2024
BACKGROUND: Artificial intelligence (AI) is increasingly used for prevention, diagnosis, monitoring, and treatment of cardiovascular diseases. Despite the potential for AI to improve care, ethical concerns and mistrust in AI-enabled healthcare exist ...
Conv-RGNN: An efficient Convolutional Residual Graph Neural Network for ECG classification.
Computer methods and programs in biomedicine
Sep 3, 2024
BACKGROUND AND OBJECTIVE: Electrocardiogram (ECG) analysis is crucial in diagnosing cardiovascular diseases (CVDs). It is important to consider both temporal and spatial features in ECG analysis to improve automated CVDs diagnosis. Significant progre...
A Scoping Review of Machine-Learning Derived Radiomic Analysis of CT and PET Imaging to Investigate Atherosclerotic Cardiovascular Disease.
Tomography (Ann Arbor, Mich.)
Sep 3, 2024
BACKGROUND: Cardiovascular disease affects the carotid arteries, coronary arteries, aorta and the peripheral arteries. Radiomics involves the extraction of quantitative data from imaging features that are imperceptible to the eye. Radiomics analysis ...
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