Anna L Silverman, Madhumita Sushil, Balu Bhasuran, Dana Ludwig, James Buchanan, Rebecca Racz, Mahalakshmi Parakala, Samer El-Kamary, Ohenewaa Ahima, Artur Belov, Lauren Choi, Monisha Billings, Yan Li, Nadia Habal, Qi Liu, Jawahar Tiwari, Atul J Butte, Vivek A Rudrapatna
BACKGROUND AND AIMS: Outpatient clinical notes are a rich source of information regarding drug safety. However, data in these notes are currently underutilized for pharmacovigilance due to methodological limitations in text mining. Large language models (LLM) like BERT have shown progress in a range of natural language processing tasks but have not yet been evaluated on adverse event detection. METHODS: We adapted a new clinical LLM, UCSF BERT, to identify serious adverse events (SAEs) occurring after treatment with a non-steroid immunosuppressant for inflammatory bowel disease (IBD)...
September 8, 2023: medRxiv