| Literature DB >> 35175849 |
Demilade A Adedinsewo1, Amy W Pollak1, Sabrina D Phillips1, Taryn L Smith2, Anna Svatikova3, Sharonne N Hayes4, Sharon L Mulvagh4,5, Colleen Norris6, Veronique L Roger4,7,8, Peter A Noseworthy4, Xiaoxi Yao9, Rickey E Carter10.
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.Entities:
Keywords: artificial intelligence; cardiovascular diseases; deep learning; female; humans; sex; women's health
Mesh:
Year: 2022 PMID: 35175849 PMCID: PMC8889564 DOI: 10.1161/CIRCRESAHA.121.319876
Source DB: PubMed Journal: Circ Res ISSN: 0009-7330 Impact factor: 23.213