Cardiovascular Disease Screening in Women: Leveraging Artificial Intelligence and Digital Tools
Autor: | 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 |
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Rok vydání: | 2022 |
Předmět: | |
Zdroj: | Circ Res |
ISSN: | 1524-4571 0009-7330 |
DOI: | 10.1161/circresaha.121.319876 |
Popis: | 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. |
Databáze: | OpenAIRE |
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