Medical Concept Mention Identification in Social Media Posts Using a Small Number of Sample References
Vasudevan Nedumpozhimana, Sneha Rautmare, Meegan Gower, Nishtha Jain, Maja Popović, Patricia Buffini, John Kelleher
Abstract
Identification of mentions of medical concepts in social media text can provide useful information for caseload prediction of diseases like Covid-19 and Measles. We propose a simple model for the automatic identification of the medical concept mentions in the social media text. We validate the effectiveness of the proposed model on Twitter, Reddit, and News/Media datasets.- Anthology ID:
- 2023.ranlp-1.84
- Volume:
- Proceedings of the 14th International Conference on Recent Advances in Natural Language Processing
- Month:
- September
- Year:
- 2023
- Address:
- Varna, Bulgaria
- Editors:
- Ruslan Mitkov, Galia Angelova
- Venue:
- RANLP
- SIG:
- Publisher:
- INCOMA Ltd., Shoumen, Bulgaria
- Note:
- Pages:
- 777–784
- Language:
- URL:
- https://aclanthology.org/2023.ranlp-1.84
- DOI:
- Cite (ACL):
- Vasudevan Nedumpozhimana, Sneha Rautmare, Meegan Gower, Nishtha Jain, Maja Popović, Patricia Buffini, and John Kelleher. 2023. Medical Concept Mention Identification in Social Media Posts Using a Small Number of Sample References. In Proceedings of the 14th International Conference on Recent Advances in Natural Language Processing, pages 777–784, Varna, Bulgaria. INCOMA Ltd., Shoumen, Bulgaria.
- Cite (Informal):
- Medical Concept Mention Identification in Social Media Posts Using a Small Number of Sample References (Nedumpozhimana et al., RANLP 2023)
- PDF:
- https://preview.aclanthology.org/add_acl24_videos/2023.ranlp-1.84.pdf