AI Medical Compendium Topic:
Cardiovascular Diseases

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[Research on the cardiovascular function evaluation system based on noninvasive detection indices].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
Based on the noninvasive detection indeices and fuzzy mathematics method, this paper studied the noninvasive, convenient and economical cardiovascular health assessment system. The health evaluation index of cardiovascular function was built based on...

Using Machine Learning to Integrate Socio-Behavioral Factors in Predicting Cardiovascular-Related Mortality Risk.

Studies in health technology and informatics
Cardiovascular disease is prevalent and associated with significant mortality rate. Robust lifetime risk stratification for cardiovascular disease is important for effective prevention, early diagnoses, targeted intervention, and improved prognosis. ...

State-of-the-Art Deep Learning in Cardiovascular Image Analysis.

JACC. Cardiovascular imaging
Cardiovascular imaging is going to change substantially in the next decade, fueled by the deep learning revolution. For medical professionals, it is important to keep track of these developments to ensure that deep learning can have meaningful impact...

Cardiovascular disease diagnosis using cross-domain transfer learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
While cardiovascular diseases (CVDs) are commonly diagnosed by cardiologists via inspecting electrocardiogram (ECG) waveforms, these decisions can be supported by a data-driven approach, which may automate this process. An automatic diagnostic approa...

Machine Learning and Deep Neural Networks in Thoracic and Cardiovascular Imaging.

Journal of thoracic imaging
Advances in technology have always had the potential and opportunity to shape the practice of medicine, and in no medical specialty has technology been more rapidly embraced and adopted than radiology. Machine learning and deep neural networks promis...

An outcome model approach to transporting a randomized controlled trial results to a target population.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Participants enrolled into randomized controlled trials (RCTs) often do not reflect real-world populations. Previous research in how best to transport RCT results to target populations has focused on weighting RCT data to look like the tar...