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Cardiovascular Disease Screening in Women: Leveraging Artificial Intelligence and Digital Tools.
Adedinsewo, Demilade A; Pollak, Amy W; Phillips, Sabrina D; Smith, Taryn L; Svatikova, Anna; Hayes, Sharonne N; Mulvagh, Sharon L; Norris, Colleen; Roger, Veronique L; Noseworthy, Peter A; Yao, Xiaoxi; Carter, Rickey E.
Afiliação
  • Adedinsewo DA; Department of Cardiovascular Medicine (D.A.A., A.W.P., S.D.P.), Mayo Clinic, Jacksonville, FL.
  • Pollak AW; Department of Cardiovascular Medicine (D.A.A., A.W.P., S.D.P.), Mayo Clinic, Jacksonville, FL.
  • Phillips SD; Department of Cardiovascular Medicine (D.A.A., A.W.P., S.D.P.), Mayo Clinic, Jacksonville, FL.
  • Smith TL; Division of General Internal Medicine (T.L.S.), Mayo Clinic, Jacksonville, FL.
  • Svatikova A; Department of Cardiovascular Diseases (A.S.), Mayo Clinic, Phoenix, AZ.
  • Hayes SN; Department of Cardiovascular Medicine (S.N.H., S.L.M., V.L.R., P.A.N.), Mayo Clinic, Rochester, MN.
  • Mulvagh SL; Department of Cardiovascular Medicine (S.N.H., S.L.M., V.L.R., P.A.N.), Mayo Clinic, Rochester, MN.
  • Norris C; Division of Cardiology, Dalhousie University, Halifax, Nova Scotia, Canada (S.L.M.).
  • Roger VL; Cardiovascular Health and Stroke Strategic Clinical Network, Edmonton, Canada (C.N.).
  • Noseworthy PA; Department of Cardiovascular Medicine (S.N.H., S.L.M., V.L.R., P.A.N.), Mayo Clinic, Rochester, MN.
  • Yao X; Department of Quantitative Health Sciences (V.L.R.), Mayo Clinic, Rochester, MN.
  • Carter RE; Epidemiology and Community Health Branch, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, MD (V.L.R.).
Circ Res ; 130(4): 673-690, 2022 02 18.
Article em En | MEDLINE | ID: mdl-35175849
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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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Inteligência Artificial / Doenças Cardiovasculares / Programas de Rastreamento / Tecnologia Digital Tipo de estudo: Diagnostic_studies / Guideline / Prognostic_studies / Risk_factors_studies / Screening_studies Limite: Female / Humans / Pregnancy Idioma: En Revista: Circ Res Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Inteligência Artificial / Doenças Cardiovasculares / Programas de Rastreamento / Tecnologia Digital Tipo de estudo: Diagnostic_studies / Guideline / Prognostic_studies / Risk_factors_studies / Screening_studies Limite: Female / Humans / Pregnancy Idioma: En Revista: Circ Res Ano de publicação: 2022 Tipo de documento: Article