Over the past year and a half, our hospitals, overwhelmed by COVID-19 patients desperate for oxygen, have been debilitated by staff and resource shortages. While many called for vaccines as a hopeful cure-all, some recognized a faster alternative: efficient and deliberate distribution of hospital resources. Fourth-year PhD candidate Amogh Hiremath and Professor of Biomedical Engineering Anant Madabhushi at ǿմý were among the bioengineers who confronted this problem. “It’s particularly heart-wrenching, as a father myself, to see pediatric wards filled up… kids [who] require critical surgeries just don’t have a bed,” Madabhushi said. Recognizing that delayed or inaccurate risk assessments could prove fatal, Hiremath and Madabhushi CIAIN (integrated clinical and AI imaging nomogram), the first deep-learning algorithm to predict the severity of COVID-19 patients’ prognoses based on patient CT lung scans as well as clinical factors.
Article Date
November 18, 2021