Improving Biomedical Question Answering by Data Augmentation and Model Weighting
Author:
Affiliation:
1. Faculty of Information Technology, Beijing University of Technology, Beijing, China
Funder
Beijing Natural Science Foundation
National Key R&D Program of China
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Applied Mathematics,Genetics,Biotechnology
Link
http://xplorestaging.ieee.org/ielx7/8857/10091711/09765710.pdf?arnumber=9765710
Reference30 articles.
1. Improving Multi-hop Question Answering over Knowledge Graphs using Knowledge Base Embeddings
2. RikiNet: Reading Wikipedia Pages for Natural Question Answering
3. Knowledge Abstraction Matching for Medical Question Answering
4. Learning to Identify Follow-Up Questions in Conversational Question Answering
5. Adversarial Examples for Evaluating Reading Comprehension Systems
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2. Bridging the gap in biomedical information retrieval: Harnessing machine learning for enhanced search results and query semantics;Journal of Intelligent & Fuzzy Systems;2024-04-18
3. Question answering systems for health professionals at the point of care—a systematic review;Journal of the American Medical Informatics Association;2024-02-16
4. BioBERT for Multiple Knowledge-Based Question Expansion and Biomedical Extractive Question Answering;Lecture Notes in Computer Science;2024
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