Current models of mortality risk after heart failure (HF) rely primarily on cardiac-specific clinical variables and may underestimate risk in elderly East Asian patients. Researchers from Japan used ...

“Bad,” or LDL, cholesterol is a major risk factor for heart disease and most people are screened for it as part of their yearly physicals. There’s another marker in the blood that may be a better ...

Larry Allen, MD, MHS, and Kenneth B Margulies, MD, discuss HF management for American Heart Month and Heart Failure Awareness Week. Advances in heart failure research and management have led to ...

This module contains the Python code (version 1.0) of the manuscript: Machine learning for smell: Ordinal odor strength prediction of molecular perfumery components (DOI coming soon). It implements ...

Objectives Earlier heart failure (HF) diagnosis in the community could allow timely treatment initiation and prevent unnecessary hospitalisation, but identifying those at risk remains challenging. We ...

Risk for a composite heart failure outcome was reduced by 22% with oral semaglutide in heart failure patients with type 2 diabetes and certain comorbidities, a secondary analysis of a ...

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The PlayStation 4 version will be a digital-only release.

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Abstract: Machine learning provides a powerful way of predicting heart failure by identifying hidden patterns using clinical parameters, which is made possible by the abundance of healthcare data.