Dr. Partho Sengupta, Abnash C. Jain chair and chief of the Division of Cardiology and director of Cardiovascular Imaging at the West Virginia University School of Medicine (WVU Photo)
Doctors and other health care providers could get some help from artificial intelligence, which could expedite decisions regarding patient care and minimize exposure, saving personal protective equipment, according to Dr. Partho Sengupta, Abnash C. Jain chair and chief of the Division of Cardiology and director of Cardiovascular Imaging at the West Virginia University School of Medicine.
Quotes and Comments:
“Advances in artificial intelligence in cardiology can be an efficient tool to fast track decisions for providers, alleviating some of the burden on an overstressed medical system operating at capacity. It could also help providers determine when patient contact is actually required, which will conserve personal protective equipment and reduce provider exposure when caring for patients who are COVID-19 positive with underlying cardiac problems.”
“Approximately 20 to 25 percent of patients diagnosed with COVID-19 will have heart-related complications, and utilizing artificial intelligence can fast-track decisions while minimizing exposure.”
“It’s a hot topic in the medical community, and grant funding has been awarded to researchers to help refine how we use these technologies. It has significant implications for not only the current situation, but for healthcare in the long run.” – Dr. Partho Sengupta, Abnash C. Jain Chair and Chief of the Division of Cardiology and Director of Cardiovascular Imaging
Resources:
Sengupta and his team have published numerous times on the topic of cardiovascular artificial intelligence recently, ranging from screening technologies to advance decision making tools that have increasing relevance in the current COVID-19 pandemic:
Nature -- AI tracks a beating heart’s function over time
Journal of American College of Cardiology: Cardiovascular Imaging -- Network-based ‘phenomics’ approach for discovering patient subtypes from high-throughput cardiac imaging data
Journal of American College of Cardiology: Cardiovascular Imaging -- Interpatient similarities in cardiac function: A platform for personalized cardiovascular medicine
Target Audiences:
- General public
- Healthcare providers
- Academic community
-WVU-
zl/04/15/20
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