2 citations · 2 across the 3 of their papers we have counts for
5 papers
Assessment of Non-Institutional AI Tool Usage Among Clinicians
Sarah Pungitore, Jarrod Mosier
Generative artificial intelligence (AI) tools are increasingly accessible and have the potential to improve efficiency across clinical workflows. However, clinicians may also use n…
Lightweight Language Models are Prone to Reasoning Errors for Complex Computational Phenotyping Tasks
Sarah Pungitore, Shashank Yadav, David Maughan +1
Although computational phenotyping is a central informatics activity with resulting cohorts supporting a wide variety of applications, it is time-intensive because of manual data r…
SHREC: A Framework for Advancing Next-Generation Computational Phenotyping with Large Language Models
Sarah Pungitore, Shashank Yadav, Molly Douglas +2
Computational phenotyping is a central informatics activity with resulting cohorts supporting a wide variety of applications. However, it is time-intensive because of manual data r…
PHEONA: An Evaluation Framework for Large Language Model-based Approaches to Computational Phenotyping
Sarah Pungitore, Shashank Yadav, Vignesh Subbian
Computational phenotyping is essential for biomedical research but often requires significant time and resources, especially since traditional methods typically involve extensive m…
Computable Phenotypes for Post-acute sequelae of SARS-CoV-2: A National COVID Cohort Collaborative Analysis
Sarah Pungitore, Toluwanimi Olorunnisola, Jarrod Mosier +1
Post-acute sequelae of SARS-CoV-2 (PASC) is an increasingly recognized yet incompletely understood public health concern. Several studies have examined various ways to phenotype PA…