Integrating Surgical Risk Prediction Tools into Clinical Workflows - Topics in Surgical Informatics скачать в хорошем качестве

Integrating Surgical Risk Prediction Tools into Clinical Workflows - Topics in Surgical Informatics

In this month's Surgical Informatics Lab journal club, one of the lab's postdoctoral fellows Jayson Marwaha discusses the following paper: Performance of a Machine Learning Algorithm Using Electronic Health Record Data to Predict Postoperative Complications and Report on a Mobile Platform: https://jamanetwork.com/journals/jama... We are joined by one of the paper's authors Dr. Tyler Loftus, assistant professor of surgery and acute care surgeon at the University of Florida. We discuss how surgical risk prediction tools might be integrated into clinical workflows, how they can be used to change surgeons' risk assessments and decisions, and how the uncertainty of algorithmic predictions can be measured and communicated. The Surgical Informatics Lab is a research lab at Beth Israel Deaconess Medical Center (BIDMC) and Harvard Medical School (HMS) in Boston, MA focused on improving the care of surgical patients with data science. The lab is run by Dr. Gabriel Brat, a trauma surgeon, intensivist, and assistant professor of surgery at Beth Israel Deaconess Medical Center and instructor of biomedical informatics at Harvard Medical School. Original recording date: June 15, 2022