American Heart Journal Plus (Jan 2022)

Establishing an interdisciplinary research team for cardio-oncology artificial intelligence informatics precision and health equity

  • Sherry-Ann Brown,
  • Rodney Sparapani,
  • Kristen Osinski,
  • Jun Zhang,
  • Jeffrey Blessing,
  • Feixiong Cheng,
  • Abdulaziz Hamid,
  • Generika Berman,
  • Kyla Lee,
  • Mehri BagheriMohamadiPour,
  • Jessica Castrillon Lal,
  • Anai N. Kothari,
  • Pedro Caraballo,
  • Peter Noseworthy,
  • Roger H. Johnson,
  • Kathryn Hansen,
  • Louise Y. Sun,
  • Bradley Crotty,
  • Yee Chung Cheng,
  • Jessica Olson

Journal volume & issue
Vol. 13
p. 100094

Abstract

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Study objective: A multi-institutional interdisciplinary team was created to develop a research group focused on leveraging artificial intelligence and informatics for cardio-oncology patients. Cardio-oncology is an emerging medical field dedicated to prevention, screening, and management of adverse cardiovascular effects of cancer/cancer therapies. Cardiovascular disease is a leading cause of death in cancer survivors. Cardiovascular risk in these patients is higher than in the general population. However, prediction and prevention of adverse cardiovascular events in individuals with a history of cancer/cancer treatment is challenging. Thus, establishing an interdisciplinary team to create cardiovascular risk stratification clinical decision aids for integration into electronic health records for oncology patients was considered crucial. Design/setting/participants: Core team members from the Medical College of Wisconsin (MCW), University of Wisconsin-Milwaukee (UWM), and Milwaukee School of Engineering (MSOE), and additional members from Cleveland Clinic, Mayo Clinic, and other institutions have joined forces to apply high-performance computing in cardio-oncology. Results: The team is comprised of clinicians and researchers from relevant complementary and synergistic fields relevant to this work. The team has built an epidemiological cohort of ~5000 cancer survivors that will serve as a database for interdisciplinary multi-institutional artificial intelligence projects. Conclusion: Lessons learned from establishing this team, as well as initial findings from the epidemiology cohort, are presented. Barriers have been broken down to form a multi-institutional interdisciplinary team for health informatics research in cardio-oncology. A database of cancer survivors has been created collaboratively by the team and provides initial insight into cardiovascular outcomes and comorbidities in this population.

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