Cardiovascular Disease Screening in Women: Leveraging Artificial Intelligence and Digital Tools

Demilade A. Adedinsewo; Amy W. Pollak; Sabrina D. Phillips; Taryn L. Smith; Anna Svatikova; Sharonne N. Hayes; Sharon L. Mulvagh; Colleen Norris; Veronique L. Roger; Peter A. Noseworthy; Xiaoxi Yao; Rickey E. Carter

doi:10.1161/CIRCRESAHA.121.319876

Cardiovascular Disease Screening in Women: Leveraging Artificial Intelligence and Digital Tools

Demilade A. Adedinsewo, Amy W. Pollak, Sabrina D. Phillips, Taryn L. Smith, Anna Svatikova, Sharonne N. Hayes, Sharon L. Mulvagh, Colleen Norris, Veronique L. Roger, Peter A. Noseworthy, Xiaoxi Yao, Rickey E. Carter

Medicine

Résultat de recherche: Article › examen par les pairs

41 Citations (Scopus)

Résumé

Cardiovascular disease remains the leading cause of death in women. Given accumulating evidence on sex- and gender-based differences in cardiovascular disease development and outcomes, the need for more effective approaches to screening for risk factors and phenotypes in women is ever urgent. Public health surveillance and health care delivery systems now continuously generate massive amounts of data that could be leveraged to enable both screening of cardiovascular risk and implementation of tailored preventive interventions across a woman's life span. However, health care providers, clinical guidelines committees, and health policy experts are not yet sufficiently equipped to optimize the collection of data on women, use or interpret these data, or develop approaches to targeting interventions. Therefore, we provide a broad overview of the key opportunities for cardiovascular screening in women while highlighting the potential applications of artificial intelligence along with digital technologies and tools.

Langue d'origine	English
Pages (de-à)	673-690
Nombre de pages	18
Journal	Circulation Research
Volume	130
Numéro de publication	4
DOI	https://doi.org/10.1161/CIRCRESAHA.121.319876
Statut de publication	Published - févr. 18 2022

Note bibliographique

Funding Information:
D.A. Adedinsewo receives research support from the Mayo Clinic Women’s Health Research Center and the Mayo Clinic Building Interdisciplinary Research Careers in Women’s Health program funded by the National Institutes of Health (grant No. K12 HD065987). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Publisher Copyright:
© 2022 Lippincott Williams and Wilkins. All rights reserved.

ASJC Scopus Subject Areas

Physiology
Cardiology and Cardiovascular Medicine

PubMed: MeSH publication types

Journal Article
Research Support, N.I.H., Extramural
Review

ODD de l’ONU

Cette action contribue à la réalisation des objectifs de développement durable suivants

Accès au document

10.1161/CIRCRESAHA.121.319876

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abstract = "Cardiovascular disease remains the leading cause of death in women. Given accumulating evidence on sex- and gender-based differences in cardiovascular disease development and outcomes, the need for more effective approaches to screening for risk factors and phenotypes in women is ever urgent. Public health surveillance and health care delivery systems now continuously generate massive amounts of data that could be leveraged to enable both screening of cardiovascular risk and implementation of tailored preventive interventions across a woman's life span. However, health care providers, clinical guidelines committees, and health policy experts are not yet sufficiently equipped to optimize the collection of data on women, use or interpret these data, or develop approaches to targeting interventions. Therefore, we provide a broad overview of the key opportunities for cardiovascular screening in women while highlighting the potential applications of artificial intelligence along with digital technologies and tools.",

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Cardiovascular Disease Screening in Women: Leveraging Artificial Intelligence and Digital Tools

Résumé

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PubMed: MeSH publication types

ODD de l’ONU

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