New AI tool will predict patients at high risk for opioid use disorder and overdose
UF researchers will use data from patients’ electronic medical records to help clinicians safely and effectively prescribe opioid medications.
Posts tagged as
LoCiganic
Machine-learning algorithm led by UF researcher improves the prediction of opioid overdose by integrating health claims data with public human services data
The study led by Dr. Weihsuan "Jenny" Lo-Ciganic was published by PLOS One.
Drs. Lo-Ciganic and Hincapie-Castillo appointed as section co-editors for Pain Medicine journal
Pain Medicine is a multidisciplinary journal dedicated to pain clinicians, educators and researchers with an interest in pain from various medical specialties.
Dr. Weihsuan “Jenny” Lo-Ciganic to lead virtual ISPOR workshop on machine learning
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 “Jenny”…
Dr. Weihsuan “Jenny” Lo-Ciganic wins UF Excellence Award for Assistant Professors
The UF Excellence Award for Assistant Professors is one of the university’s top awards for a junior faculty member.
UF, Genentech, and conference collaboration leads workshop offered at Virtual ISPOR 2020
The virtual workshop will address how machine learning and data mining techniques can enhance health economics outcomes research.
Meta-analysis led by UF researchers compares different treatment options for advanced melanoma
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.
Dr. Lo Ciganic receives National Institute on Aging grant to study opioid and benzodiazepine use among older adults
Lo-Ciganic's research team will develop a real-time trajectory tool to identify potentially unsafe concurrent opioid and benzodiazepine use among older adults.
New machine-learning model found effective at predicting risk of opioid overdose
The model allows scientists to assess complex interactions of large data that can reveal hidden patterns and generate more accurate predictions in clinical settings.
