Parisa Rashidi is the founding co-director of the Intelligent Critical Care Center and an associate professor at the J. Crayton Pruitt Family Department of Biomedical Engineering. She is also affiliated with the Electrical & Computer Engineering and Computer & Information Science & Engineering departments.She specializes in intelligent patient monitoring systems using artificial intelligence and sensing technology.
Areas of Expertise (5)
Machine Learning for Health
Medicine Artificial Intelligence (AI)
Media Appearances (1)
NBC Nightly News covers IC3’s medical AI advances
NBC Nightly News tv
On Saturday, February 4, 2023, Intelligent Critical Care Center (IC3) co-directors Azra Bihorac and Parisa Rashidi appeared on NBC Nightly News in a segment with Dr. John Torres to discuss the Center’s research into using AI to monitor the status of critically ill patients. “This technology takes a big burden off physicians and nurses,” Bihorac said, “and provides them time to actually engage in what we are here for—taking care of patients.”
Digital Health Transformers and Opportunities for Artificial Intelligence–Enabled NephrologyClinical Journal of the American Society of Nephrology
Benjamin Shickel, et. al
The rapid evolution of clinical artificial intelligence (AI) has been spurred by the increasing scope and scale of digital patient data and the emergence and adaptation of specialized machine learning (ML) algorithms. Among others, the field of nephrology is poised to become a prime benefactor of the medical AI revolution, with several retrospective studies highlighting the potential for augmented clinical decision support through data-driven phenotyping and earlier and more accurate prediction of...
Postoperative Overtriage to an Intensive Care Unit Is Associated With Low Value of CareAnnals of Surgery
Tyler J. Loftus, et. al
Objective: We test the hypothesis that for low-acuity surgical patients, postoperative intensive care unit (ICU) admission is associated with lower value of care compared with ward admission. Background: Overtriaging low-acuity patients to ICU consumes valuable resources and may not confer better patient outcomes. Associations among postoperative overtriage, patient outcomes, costs, and value of care have not been previously reported.
Human activity recognition in artificial intelligence framework: a narrative reviewArtifical Intelligence Review
Neha Gupta, et. al
Human activity recognition (HAR) has multifaceted applications due to its worldly usage of acquisition devices such as smartphones, video cameras, and its ability to capture human activity data. While electronic devices and their applications are steadily growing, the advances in Artificial intelligence (AI) have revolutionized the ability to extract deep hidden information for accurate detection and its interpretation.