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

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish (US)
Pages (from-to)673-690
Number of pages18
JournalCirculation research
Issue number4
StatePublished - Feb 18 2022


  • artificial intelligence
  • cardiovascular diseases
  • deep learning
  • female
  • humans
  • sex
  • women's health

ASJC Scopus subject areas

  • Physiology
  • Cardiology and Cardiovascular Medicine


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