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Cardiovascular Diseases

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Polysocial Risk Scores: Implications for Cardiovascular Disease Risk Assessment and Management.

Current atherosclerosis reports
PURPOSE OF REVIEW: To review current evidence, discuss key knowledge gaps and identify opportunities for development, validation and application of polysocial risk scores (pSRS) for cardiovascular disease (CVD) risk prediction and population cardiova...

A comprehensive review of applications of artificial intelligence in echocardiography.

Current problems in cardiology
Echocardiography plays a crucial role in diagnosis of cardiovascular diseases. Artificial intelligence has emerged as a high-precision tool to automate echocardiographic analysis. This review discusses AI algorithms that have been utilized at various...

The leading global health challenges in the artificial intelligence era.

Frontiers in public health
Millions of people's health is at risk because of several factors and multiple overlapping crises, all of which hit the vulnerable the most. These challenges are dynamic and evolve in response to emerging health challenges and concerns, which need ef...

Can ChatGPT provide appropriate meal plans for NCD patients?

Nutrition (Burbank, Los Angeles County, Calif.)
OBJECTIVES: Dietary habits significantly affect health conditions and are closely related to the onset and progression of non-communicable diseases (NCDs). Consequently, a well-balanced diet plays an important role in lessening the effects of various...

Predicting incident cardiovascular disease among African-American adults: A deep learning approach to evaluate social determinants of health in the Jackson heart study.

PloS one
The present study sought to leverage machine learning approaches to determine whether social determinants of health improve prediction of incident cardiovascular disease (CVD). Participants in the Jackson Heart study with no history of CVD at baselin...

Deep-learning-based natural-language-processing models to identify cardiovascular disease hospitalisations of patients with diabetes from routine visits' text.

Scientific reports
Writing notes is the most widespread method to report clinical events. Therefore, most of the information about the disease history of a patient remains locked behind free-form text. Natural language processing (NLP) provides a solution to automatica...

Vascular Age Assessed From an Uncalibrated, Noninvasive Pressure Waveform by Using a Deep Learning Approach: The AI-VascularAge Model.

Hypertension (Dallas, Tex. : 1979)
BACKGROUND: Aortic stiffness, assessed as carotid-femoral pulse wave velocity, provides a measure of vascular age and risk for adverse cardiovascular disease outcomes, but it is difficult to measure. The shape of arterial pressure waveforms conveys i...

Cardiac arrhythmia detection using deep learning approach and time frequency representation of ECG signals.

BMC medical informatics and decision making
BACKGROUND: Cardiac arrhythmia is a cardiovascular disorder characterized by disturbances in the heartbeat caused by electrical conduction anomalies in cardiac muscle. Clinically, ECG machines are utilized to diagnose and monitor cardiac arrhythmia n...

Artificial Intelligence in the Prevention and Detection of Cardiovascular Disease.

Cardiology in review
For more than 60 years, artificial intelligence (AI) has served as a mainstay in augmenting and assisting the lives of individuals across a wide array of interests and professional fields. Functioning to create deep computer simulations, analyze data...

Integrating street view images and deep learning to explore the association between human perceptions of the built environment and cardiovascular disease in older adults.

Social science & medicine (1982)
Understanding how built environment attributes affect health remains important. While many studies have explored the objective characteristics of built environments that affect health outcomes, few have examined the role of human perceptions of built...