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Beyond traditional scores: a critical look at machine learning approaches in cardiovascular risk assessment.

Year: 2025

Type: article

Abstract: Risk scores for incident cardiovascular disease (CVD) are recommended by various clinical guidelines to inform decisions about preventive interventions1. Traditionally, these risk scores have been developed using regression-based methods2,3. Recent years have seen increasing numbers of models developed using machine learning (ML) or artificial intelligence (AI) techniques, but few are currently recommended by clinical guidelines for routine use.

Source: Apollo (University of Cambridge)

DOI: 10.17863/cam.119135

Authors: Keene, Spencer J, Kaptoge, Stephen, Pennells, Lisa

Language: English

Topic: Artificial Intelligence in Healthcare

Subfield: Health Information Management

Field: Health Professions

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: green

Funders: National Institute for Health and Care Research, British Heart Foundation