< content="width=device-width, initial-scale=1.0"> Dr. Kelvin Kan Featured in Anesthesiology News for Work on Machine Learning in Sepsis Identification | Anesthesiology Department | U of U School of Medicine
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Dr. Kelvin Kan Featured in Anesthesiology News for Work on Machine Learning in Sepsis Identification

Dr. Kelvin Kan Featured in Anesthesiology News for Work on Machine Learning in Sepsis Identification

We are proud to announce that Dr. Kelvin Kan, one of our department’s residents, was recently featured in Anesthesiology News in an article titled, "Machine Learning Can Aid in Sepsis Identification." The article highlights Dr. Kan’s innovative research on a novel, integer-based machine learning model designed to assist in the early diagnosis of in-hospital sepsis.

In the interview, Dr. Kan discussed his abstract presented at the International Anesthesia Research Society (IARS) and the ongoing development of his project. The machine learning model holds great potential in reducing patient morbidity and mortality by facilitating timely identification of sepsis, which is a key factor in improving patient outcomes.

We are thrilled to see Dr. Kan’s contributions to the integration of machine learning in anesthesiology and look forward to the continued progress of this promising research.

A portrait of Dr. Kan next to text that reads, "Anesthesiology Resident, Dr. Kelvin Kan, Featured in Anesthesiology News for Work on Machine Learning in Sepsis Identification."