UF researchers will use data from patients’ electronic medical records to help clinicians safely and effectively prescribe opioid medications.
The study led by Dr. Weihsuan "Jenny" Lo-Ciganic was published by PLOS One.
Pain Medicine is a multidisciplinary journal dedicated to pain clinicians, educators and researchers with an interest in pain from various medical specialties.
Weihsuan “Jenny” Lo-Ciganic, Ph.D., M.S., M.S.Pharm., will lead a short course workshop on machine learning as part of the International Society for Pharmacoeconomics and Outcomes Research’s Virtual ISPOR 2020 Conference from 10 a.m. to 3 p.m. EST on Monday, July 27. Weishuan…
The UF Excellence Award for Assistant Professors is one of the university’s top awards for a junior faculty member.
The virtual workshop will address how machine learning and data mining techniques can enhance health economics outcomes research.
The study was published in JAMA Open Network and its findings may be valuable for clinical decision-making regarding treatment regimen selection for individuals with advanced melanoma.
Lo-Ciganic's research team will develop a real-time trajectory tool to identify potentially unsafe concurrent opioid and benzodiazepine use among older adults.
The model allows scientists to assess complex interactions of large data that can reveal hidden patterns and generate more accurate predictions in clinical settings.