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Found 5 papers, 3 papers with code
UCSD-Adobe at MEDIQA 2021: Transfer Learning and Answer Sentence Selection for Medical Summarization
We show that both transfer learning methods combined achieve the highest ROUGE scores.
Joint Summarization-Entailment Optimization for Consumer Health Question Understanding
Understanding the intent of medical questions asked by patients, or Consumer Health Questions, is an essential skill for medical Conversational AI systems.
Medical Question Understanding and Answering with Knowledge Grounding and Semantic Self-Supervision
The system first matches the summarized user question with an FAQ from a trusted medical knowledge base, and then retrieves a fixed number of relevant sentences from the corresponding answer document.
Recursive Tree-Structured Self-Attention for Answer Sentence Selection
The recursive nature of our model is able to represent all levels of syntactic parse trees with only one additional self-attention layer.
A Gradually Soft Multi-Task and Data-Augmented Approach to Medical Question Understanding
Users of medical question answering systems often submit long and detailed questions, making it hard to achieve high recall in answer retrieval.
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