4 citations · 4 across the 7 of their papers we have counts for
4 papers · 1 filter
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…
Failure Modes of Time Series Interpretability Algorithms for Critical Care Applications and Potential Solutions
Shashank Yadav, Vignesh Subbian
Interpretability plays a vital role in aligning and deploying deep learning models in critical care, especially in constantly evolving conditions that influence patient survival. H…
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…