Washington University in St. Louis researchers and clinicians have been incorporating data from Fitbit wristbands into machine-learning models that could predict surgical outcomes, pain after surgery and potential mental health issues, among other uses. While working with clinicians to predict pancreatic surgery outcomes, WashU researchers encountered an unexpected factor that changed their prediction model: the COVID-19 pandemic.
The pandemic disrupted daily life, from school and work to medical procedures, including pancreatic surgery, which can be complex with risks for complications and a challenging recovery. While it may be difficult for clinicians to determine who might be a good candidate for such surgery and who has a good prognosis for recovery, they may get some insight from using a model that analyzes patient data from their electronic health record as well as from a Fitbit wristband, a previous study published in 2021 revealed.
In a follow-up study, Jingwen Zhang, who earned a doctorate in computer science from the McKelvey School of Engineering in 2024 in the lab of Chenyang Lu, the Fullgraf Professor in computer science and engineering and director of the AI for Health Institute, found that their model performed better to predict the outcome of patients who had pancreatic surgery before the COVID-19 pandemic than after, leading Zhang to develop a novel solution in collaboration with a multidisciplinary team of artificial intelligence (AI) researchers and surgeons.
Results of the research were published online in ACM Transactions on Computing for Healthcare Jan. 19.
Read more on the McKelvey Engineering website.
