Geisinger AI team’s entry accurately predicted long COVID risk among patients diagnosed with COVID-19
The nationwide challenge included submissions from universities, medical centers and public-private partnerships. Entrants developed artificial intelligence/machine learning (AI/ML) models and algorithms to identify which patients infected with COVID-19 had a higher likelihood of developing long COVID. Entries used de-identified electronic health records (EHR) data available through the National COVID Cohort Collaborative Data Enclave, a data repository that represents EHR data from more than 70 health centers across the United States.
People with long COVID experience a variety of symptoms that last weeks or months after a COVID-19 diagnosis. These conditions can include fatigue, respiratory issues, headaches, trouble sleeping, depression or anxiety, among many others. Predicting which patients are most likely to develop long COVID allows for earlier intervention and symptom management, leading to better overall health outcomes.
Geisinger’s AI team built a portable, efficient and accurate model using the most commonly available patient information, resulting in a long COVID prediction tool that could be easily and widely integrated into the EHR and used for population-level risk stratification. The team placed second overall in the challenge, ahead of University of California-Berkeley (3rd place), University of Wisconsin-Madison (honorable mention), and the University of Pennsylvania (honorable mention). The winning team (Convalesco) is a collaboration between the University of Chicago and Argonne National Laboratory.
“Accuracy and interpretability are the twin challenges of artificial intelligence in healthcare, and our solution was based on extensive experience deploying clinical prediction models for population health at Geisinger,” said Abdul Tariq, Ph.D., director of artificial intelligence at Geisinger.
"We're thrilled to have been a part of this national, open science project, and hope that our contribution can improve clinical identification, characterization, and quality of life for those living with long COVID," said Elliot Mitchell, Ph.D., senior data scientist and a member of Geisinger’s AI team.
Geisinger is committed to making better health easier for the more than 1 million people it serves. Founded more than 100 years ago by Abigail Geisinger, the system now includes 10 hospital campuses, a health plan with more than half a million members, a research institute and the Geisinger College of Health Sciences, which includes schools of medicine, nursing and graduate education. With more than 25,000 employees and 1,700+ employed physicians, Geisinger boosts its hometown economies in Pennsylvania by billions of dollars annually. Learn more at geisinger.org or connect with us on Facebook, Instagram, LinkedIn and Twitter.
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