We are thrilled to announce that Dr. Raja showcased her research work at the AMIA Informatics Summit 2024 held in Boston on March 20th.
Presentation Title: A Study of Biomedical Relation Extraction Using GPT Models
Abstract: Relation Extraction (RE) is a natural language processing (NLP) task for extracting semantic relations between biomedical entities. Recent developments in pre-trained large language models (LLM) motivated NLP researchers to use them for various NLP tasks. We investigated GPT-3.5-turbo and GPT-4 on extracting the relations from three standard datasets, EU-ADR, Gene Associations Database (GAD), and ChemProt. Unlike the existing approaches using datasets with masked entities, we used three versions for each dataset for our experiment: a version with masked entities, a second version with the original entities (unmasked), and a third version with abbreviations replaced with the original terms. We developed the prompts for various versions and used the chat completion model from GPT API. Our approach achieved a F1-score of 0.498 to 0.809 for GPT-3.5-turbo, and a highest F1-score of 0.84 for GPT-4. For certain experiments, the performance of GPT, BioBERT, and PubMedBERT are almost the same.
Keywords: Prompt engineering, relation extraction, generative pre-trained transformer, GPT-3.5-turbo, GPT-4
Additionally, Dr. Raja has been selected to attend a prestigious Corporate Roundtable, The Opportunities and Burdens for Next Generation Registries, to engage in discussions surrounding the challenges and opportunities inherent in next-generation registries.