Automatic Extraction of Disease Risk Factors from Medical Publications

Maxim Rubchinsky, Ella Rabinovich, Adi Shribman, Netanel Golan, Tali Sahar, Dorit Shweiki

Abstract
We present a novel approach to automating the identification of risk factors for diseases from medical literature, leveraging pre-trained models in the bio-medical domain, while tuning them for the specific task. Faced with the challenges of the diverse and unstructured nature of medical articles, our study introduces a multi-step system to first identify relevant articles, then classify them based on the presence of risk factor discussions and, finally, extract specific risk factor information for a disease through a question-answering model. Our contributions include the development of a comprehensive pipeline for the automated extraction of risk factors and the compilation of several datasets, which can serve as valuable resources for further research in this area. These datasets encompass a wide range of diseases, as well as their associated risk factors, meticulously identified and validated through a fine-grained evaluation scheme. We conducted both automatic and thorough manual evaluation, demonstrating encouraging results. We also highlight the importance of improving models and expanding dataset comprehensiveness to keep pace with the rapidly evolving field of medical research.
Anthology ID:
2024.bionlp-1.38
Volume:
Proceedings of the 23rd Workshop on Biomedical Natural Language Processing
Month:
August
Year:
2024
Address:
Bangkok, Thailand
Editors:
Dina Demner-Fushman, Sophia Ananiadou, Makoto Miwa, Kirk Roberts, Junichi Tsujii
Venues:
BioNLP | WS
SIG:
SIGBIOMED
Publisher:
Association for Computational Linguistics
Note:
Pages:
474–485
Language:
URL:
https://aclanthology.org/2024.bionlp-1.38
DOI:
Bibkey:
Cite (ACL):
Maxim Rubchinsky, Ella Rabinovich, Adi Shribman, Netanel Golan, Tali Sahar, and Dorit Shweiki. 2024. Automatic Extraction of Disease Risk Factors from Medical Publications. In Proceedings of the 23rd Workshop on Biomedical Natural Language Processing, pages 474–485, Bangkok, Thailand. Association for Computational Linguistics.
Cite (Informal):
Automatic Extraction of Disease Risk Factors from Medical Publications (Rubchinsky et al., BioNLP-WS 2024)
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