Goss, Foster R.

Using Large Language Models to Identify Social Determinants of Health to Enhance Healthcare Services and Equity

Description

This research explores using natural language processing and generative AI to capture and structure social determinants of health from patient narratives, aiming to improve data completeness and quality, enhance clinical decision support, and reduce the manual burden on clinical staff in routine care.

Grant Number
R21 HS029991
Principal Investigator(s)
Goss, Foster R.
Zhou, Li

Unsupervised clinical relevancy ranking of structured medical records to retrieve condition-specific information in the emergency department.

Citation
Korach ZT, Gradwohl S, Messinger A, Bookman K, Cohen K, Zhou L, Goss F. Unsupervised clinical relevancy ranking of structured medical records to retrieve condition-specific information in the emergency department. Int J Med Inform. 2021 May;149:104410. doi: 10.1016/j.ijmedinf.2021.104410. Epub 2021 Feb 5. PMID: 33621793.
Principal Investigator
Goss, Foster R.
Project Name
Natural Language Processing To Identify and Rank Clinically Relevant Information for EHRs in the Emergency Department

Natural Language Processing to Identify and Rank Clinically Relevant Information for EHRs in the Emergency Department - Final Report

Citation
Goss F. Natural Language Processing to Identify and Rank Clinically Relevant Information for EHRs in the Emergency Department - Final Report. (Prepared by the University of Colorado under Grant No. R21 HS024541). Rockville, MD: Agency for Healthcare Research and Quality, 2018.
Principal Investigator
Goss, Foster R.
Project Name
Natural Language Processing To Identify and Rank Clinically Relevant Information for EHRs in the Emergency Department