Sungsoo (Danny) Kim, MD, MS, PhD Candidate: Deep Learning Methods for Biomedical Image Analysis & Modeling
November 5, 2022
Sungsoo (Danny) Kim, MD, MS, PhD Candidate, CA-1 Anesthesiology Resident, was invited to present at the in Texas on November 5th. Dr. Kim's talk covered his research on the "Application of deep learning for real-time non-invasive continuous monitoring for enhanced peripheral oxygen saturation in intensive care unit (ICU) and operating room (OR)."
Non-invasive monitoring for peripheral oxygen saturation (SpO2) has been known as the fifth vital sign given its critical role in patient care in the intensive care unit (ICU) or the operating room (OR). However, a concern about the accuracy of pulse oximetry has recently attained public concern, particularly with the possible racial bias or medical discrimination in this covid-pandemic. In this research, Dr. Kim proposed an innovative approach applying Deep Neural Networks (DNNs) to develop an advanced monitoring approach for accurate oxygen saturation in a real-time manner.
Dr. Kim's research addresses key issues in mathematics and patient care. As stated by Associate Residency Program Director Christine Myo-Bui, MD, "This was a tremendous opportunity to broaden and improve our research by forging connections with professionals in the field of mathematics and engineering. Keep up the strong work Dr. Kim, and thank you for advancing the research in our field! We are proud of you!"
