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Rishi Kamaleswaran is an Associate Professor at Duke University with a focus on the application of artificial intelligence, machine learning, and data analytics in healthcare, particularly in critical care and perioperative medicine. His research includes the development of predictive models for sepsis, acute respiratory distress syndrome, and other critical conditions. By utilizing large datasets, electronic health records, and physiological waveform analysis, he aims to improve patient outcomes. His work also explores deep learning techniques for disease diagnosis, including predictions related to cardiac arrhythmias and Parkinson's disease. Additionally, Kamaleswaran's research investigates the use of wearable sensors for remote patient monitoring to enhance healthcare delivery. He collaborates with clinicians and researchers to validate and translate models into clinical practice, with an overall goal of leveraging data-driven approaches to transform healthcare and improve patient care.
Department of Biomedical Engineering (MS program)