10 citations · 24 across the 15 of their papers we have counts for
4 papers · 1 filter
Distilling Large Language Models for Efficient Clinical Information Extraction
Karthik S. Vedula, Annika Gupta, Akshay Swaminathan +3
Large language models (LLMs) excel at clinical information extraction but their computational demands limit practical deployment. Knowledge distillation--the process of transferrin…
Context Clues: Evaluating Long Context Models for Clinical Prediction Tasks on EHRs
Michael Wornow, Suhana Bedi, Miguel Angel Fuentes Hernandez +5
Foundation Models (FMs) trained on Electronic Health Records (EHRs) have achieved state-of-the-art results on numerous clinical prediction tasks. However, most existing EHR FMs hav…
ZIP-FIT: Embedding-Free Data Selection via Compression-Based Alignment
Elyas Obbad, Iddah Mlauzi, Brando Miranda +4
Data selection is crucial for optimizing language model (LM) performance on specific tasks, yet most existing methods fail to effectively consider the target task distribution. Cur…
meds_reader: A fast and efficient EHR processing library
Ethan Steinberg, Michael Wornow, Suhana Bedi +3
The growing demand for machine learning in healthcare requires processing increasingly large electronic health record (EHR) datasets, but existing pipelines are not computationally…