Date/Time
Date(s) - 10/02/2023
3:00 pm - 4:00 pm
Location
Communicore, C1-15
Because of the vast workload and patient data flow within critical care units, artificial intelligence and machine learning algorithms can be valuable tools for updating clinicians in real-time on their patients’ acuity and predicted trajectory. Visual sensing technologies can monitor patients continuously and alert clinicians to visual cues that indicate pain or that suggest an increased risk for delirium. By using sensing technologies along with deep learning to integrate clinical and physiological data with real-time autonomous assessment of visual cues, AI models can provide clinicians with continuously updated risk assessment and phenotyping for patients. Deep learning–based phenotyping has been effective in studies at identifying critical care patients at increased risk of sepsis, organ failure, and in-hospital mortality. For AI in critical care to reach its full potential in the future, work must be done now to build an infrastructure that will enable implementation of tools with real-world value for clinicians.
Bio:
I grew up in a region of northern Bosnia known for a disease called Balkan endemic nephropathy, or BEN, which causes kidney failure. My career in nephrology really began from wanting to help people from my home town suffering from kidney ailments.
I am the senior associate dean of the Office of Research in the University of Florida College of Medicine. I am also the R. Glenn Davis Professor of Medicine, Surgery, Anesthesiology and Physiology & Functional Genomics, and director of the Intelligent Critical Care Center IC3 at UF. IC3 is a multidisciplinary center focused on developing and providing sustainable support and leadership for transformative medical AI research, education, and clinical applications to advance patients’ health in critical and acute care medicine. The center uses the extensive repository of clinical and research data from UF Health, one of Florida’s largest health care systems, to support unprecedented, world-leading artificial intelligence research and innovation for transforming the diagnosis, monitoring and treatment for critically and acutely ill patients.
My vision is to develop tools for intelligent human-centered health care that delivers optimized care tailored to a patient’s “personal clinical profile” using digital data. Through my work in national and international professional organizations in nephrology and critical care medicine, I advocated for women physicians and scientists, promoting their equality and recognition in health care leadership, research and education. With the help of patients and providers alike, I believe we can create medical AI that is trustworthy and ethical.
I earned my medical degree at the University of Sarajevo School of Medicine in Sarajevo, Bosnia and Herzegovina. Then, I completed my nephrology fellowship, internal medicine residency and critical care medicine fellowship at the University of Florida. Finally, I earned my Master of Science in clinical science at UF in 2011.
I have over 200 peer-reviewed articles with more than 10,000 citations. In addition to my research, I have received notable awards from the Society of Critical Care Medicine and funding from the National Institutes of Health since 2010.
In my free time, I like hanging out with my family, reading and having discussions with my book club and traveling, nationally and internationally.