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Cardiovascular Diseases

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Enhancing Patient Education on Cardiovascular Rehabilitation with Large Language Models.

Missouri medicine
INTRODUCTION: There are barriers that exist for individuals to adhere to cardiovascular rehabilitation programs. A key driver to patient adherence is appropriately educating patients. A growing education tool is using large language models to answer ...

Adaptive wavelet base selection for deep learning-based ECG diagnosis: A reinforcement learning approach.

PloS one
Electrocardiogram (ECG) signals are crucial in diagnosing cardiovascular diseases (CVDs). While wavelet-based feature extraction has demonstrated effectiveness in deep learning (DL)-based ECG diagnosis, selecting the optimal wavelet base poses a sign...

Characterizing patients at higher cardiovascular risk for prescribed stimulants: Learning from health records data with predictive analytics and data mining techniques.

Computers in biology and medicine
OBJECTIVE: Given the significantly increased number of individuals prescribed stimulants in the past decade, there has been growing concern regarding the risk of cardiovascular events among adults on stimulant therapy. We aimed to quantify the added ...

Artificial Intelligence Applications in Cardio-Oncology: A Comprehensive Review.

Current cardiology reports
PURPOSE OF REVIEW: This review explores the role of artificial intelligence (AI) in cardio-oncology, focusing on its latest application across problems in diagnosis, prognosis, risk stratification, and management of cardiovascular (CV) complications ...

An efficient approach on risk factor prediction related to cardiovascular disease around Kumbakonam, Tamil Nadu, India, using unsupervised machine learning techniques.

Scientific reports
Nowadays, human beings suffer from varieties of diseases due to the environmental circumstances and their residing habits. Cardiovascular diseases (CVD) are the leading cause of mortality among all diseases. CVDs are heart-related diseases. In early ...

EffNet: an efficient one-dimensional convolutional neural networks for efficient classification of long-term ECG fragments.

Biomedical physics & engineering express
Early Diagnosis of Cardiovascular disease (CVD) is essential to prevent a person from death in case of a cardiac arrhythmia. Automated ECG classification is required because manual classification by cardiologists is laborious, time-consuming, and pro...

Predicting cardiovascular outcomes in Chinese patients with type 2 diabetes by combining risk factor trajectories and machine learning algorithm: a cohort study.

Cardiovascular diabetology
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...

Characterisation of cardiovascular disease (CVD) incidence and machine learning risk prediction in middle-aged and elderly populations: data from the China health and retirement longitudinal study (CHARLS).

BMC public health
BACKGROUND: Due to the ageing population and evolving lifestyles occurring in China, middle-aged and elderly populations have become high-risk groups for cardiovascular disease (CVD). The aim of this study was to analyse the incidence characteristics...

Energy-Confinement 3D Flower-Shaped Cages for AI-Driven Decoding of Metabolic Fingerprints in Cardiovascular Disease Diagnosis.

ACS nano
Rapid and accurate detection plays a critical role in improving the survival and prognosis of patients with cardiovascular disease, but traditional detection methods are far from ideal for those with suspected conditions. Metabolite analysis based on...

Unlocking the link: predicting cardiovascular disease risk with a focus on airflow obstruction using machine learning.

BMC medical informatics and decision making
BACKGROUND: Respiratory diseases and Cardiovascular Diseases (CVD) often coexist, with airflow obstruction (AO) severity closely linked to CVD incidence and mortality. As both conditions rise, early identification and intervention in risk populations...