AIMC Topic: Cardiovascular Diseases

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Integrating snapshot ensemble learning into masked autoencoders for efficient self-supervised pretraining in medical imaging.

Scientific reports
Self-supervised learning (SSL) has gained significant attention in medical imaging for its ability to leverage large amounts of unlabeled data for effective model pretraining. Among SSL methods, the masked autoencoder (MAE) has proven robust in learn...

The additive effect of the estimated glucose disposal rate and a body shape index on cardiovascular disease: A cross-sectional study.

PloS one
BACKGROUND: The glucose disposal rate (eGDR) and a body shape index (ABSI) are predictors strongly associated with cardiovascular disease (CVD) and outcomes. However, whether they have additive effects on CVD risk is unknown. This study aimed to inve...

Leveraging BERT for embedding ICD codes from large scale cardiovascular EMR data to understand patient diagnostic patterns.

BMC medical informatics and decision making
The integration of electronic medical records (EMRs) with artificial intelligence (AI) is enhancing medical research, particularly in real-world evidence (RWE) studies. Extracting insights from coded medical data, such as ICD-10 codes, is essential f...

Digital Therapeutics in Cardiovascular Healthcare: A Narrative Review.

Current cardiology reports
The rapid development of digital therapeutics (DTx) presents opportunities for cardiovascular diseases (CVD) intervention. This review aims to summarize the technologies and applications of DTx in the field of cardiovascular healthcare. It seeks to i...

Machine learning-based high-benefit approach versus traditional high-risk approach in statin therapy: the Shizuoka Kokuho database study.

Scientific reports
Statins are widely prescribed for the primary prevention of cardiovascular diseases, yet individual responses vary, necessitating personalized treatment strategies. Conventional approaches prioritize treating high-risk patients, but advancements in m...

Primary prevention cardiovascular disease risk prediction model for contemporary Chinese (1°P-CARDIAC): Model derivation and validation using a hybrid statistical and machine-learning approach.

PloS one
BACKGROUND: Cardiovascular disease (CVD) is the leading cause of mortality and morbidity in China and worldwide while we are lacking in validated primary prevention model specifically for Chinese. To identify CVD high-risk individuals for early inter...

Cardiovascular risk in psoriatic arthritis: How can we manage it?

Autoimmunity reviews
It is now widely recognized that patients with psoriatic arthritis (PsA) have a higher risk of cardiovascular disease (CVD) when compared with the general population. A number of factors contribute to this increased risk. Skin and articular inflammat...

Enhancing cardiac disease detection via a fusion of machine learning and medical imaging.

Scientific reports
Cardiovascular illnesses continue to be a predominant cause of mortality globally, underscoring the necessity for prompt and precise diagnosis to mitigate consequences and healthcare expenditures. This work presents a complete hybrid methodology that...