Quick, get me a Dr. BERT: Automatic Grading of Evidence using Transfer Learning
Pradeesh Parameswaran, Andrew Trotman, Veronica Liesaputra, David Eyers
Abstract
We describe our methods for automatically grading the level of clinical evidence in medical papers, as part of the ALTA 2021 shared task. We use a combination of transfer learning and a hand-crafted, feature-based classifier. Our system (�orangutanV3�) obtained an accuracy score of 0.4918, which placed third in the leaderboard. From our failure analysis, we find that our classification techniques do not appropriately handle cases when the conclusions of across the medical papers are themselves inconclusive. We believe that this shortcoming can be overcome�thus improving the classification accuracy�by incorporating document similarity techniques.- Anthology ID:
- 2021.alta-1.24
- Volume:
- Proceedings of the 19th Annual Workshop of the Australasian Language Technology Association
- Month:
- December
- Year:
- 2021
- Address:
- Online
- Editors:
- Afshin Rahimi, William Lane, Guido Zuccon
- Venue:
- ALTA
- SIG:
- Publisher:
- Australasian Language Technology Association
- Note:
- Pages:
- 205–212
- Language:
- URL:
- https://aclanthology.org/2021.alta-1.24
- DOI:
- Cite (ACL):
- Pradeesh Parameswaran, Andrew Trotman, Veronica Liesaputra, and David Eyers. 2021. Quick, get me a Dr. BERT: Automatic Grading of Evidence using Transfer Learning. In Proceedings of the 19th Annual Workshop of the Australasian Language Technology Association, pages 205–212, Online. Australasian Language Technology Association.
- Cite (Informal):
- Quick, get me a Dr. BERT: Automatic Grading of Evidence using Transfer Learning (Parameswaran et al., ALTA 2021)
- PDF:
- https://preview.aclanthology.org/emnlp-22-attachments/2021.alta-1.24.pdf
- Code
- prasys/orangutanv3altasharedtask21
- Data
- ALTA 2021 Shared Task