Using artificial intelligence and electronic health records to predict cardiovascular outcomes

20 Jan 2022

Written by Lana Shkak, Commissioning Editor

Artificial intelligence and machine learning Cardiopulmonary and vascular Methodology News Outcomes research

Scientists from the University of Utah (UT, USA) used Poisson Binomial-based comorbidity (PBC) to search electronic health records (EHRs) for any comorbid diagnoses, medications and procedures underlying cardiovascular health outcomes. The research, published in PLOS Digital Health, utilized the EHRs of over 1.6 million patients with diverse cardiovascular outcomes, focusing on the following three: congenital heart disease, sinoatrial node dysfunction and heart transplant. The results highlighted that PBC was effective in understanding the demographic factors and comorbidity of these key cardiovascular outcomes. The researchers believe their approach of using artificial intelligence (AI) and EHRs can demonstrate healthcare disparities present in a...