COVID-19 patients that don't believe in COVID-19, hospitals at full capacity and burnout among healthcare professionals, are just a few of the challenges that put pressure on our hospital systems, on top of the age old question, what's wrong with this patient and how do we fix it? To help solve these challenges, Dr. Karandeep uses, not only his background as a trained physician, but also his expertise in biomedical informatics. In this conversation, Assistant Professor of Learning Health Sciences, Internal Medicine, Urology, and Information at the University of Michigan, Dr. Karandeep, and Lily Adelstein discuss applications of artificial intelligence in the hospital setting.
Episode links:
Dr. Karandeep's linkedin: linkedin.com/in/kdpsingh/
Dr. Karandeep's twitter: @kdpsinghlab
Early identification of patients admitted to hospital for covid-19 at risk of clinical deterioration: model development and multisite external validation study: https://www.bmj.com/content/376/bmj-2021-068576.full
Digitising the prediction and management of sepsis: https://www.thelancet.com/journals/lancet/article/PIIS0140-6736(22)00658-4/fulltext
External Validation of a Widely Implemented Proprietary Sepsis Prediction Model in Hospitalized Patients: https://jamanetwork.com/journals/jamainternalmedicine/article-abstract/2781307
Predicting 30-day hospital readmissions using artificial neural networks with medical code embedding: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0221606