Medical Question Understanding and Answering with Knowledge Grounding and Semantic Self-Supervision

@inproceedings{Mrini2022MedicalQU,
  title={Medical Question Understanding and Answering with Knowledge Grounding and Semantic Self-Supervision},
  author={Khalil Mrini and Harpreet Singh and Franck Dernoncourt and Seunghyun Yoon and Trung Bui and Walter Chang and Emilia Farcas and Ndapa Nakashole},
  booktitle={International Conference on Computational Linguistics},
  year={2022}
}
Current medical question answering systems have difficulty processing long, detailed and informally worded questions submitted by patients, called Consumer Health Questions (CHQs). To address this issue, we introduce a medical question understanding and answering system with knowledge grounding and semantic self-supervision. Our system is a pipeline that first summarizes a long, medical, user-written question, using a supervised summarization loss. Then, our system performs a two-step retrieval… 

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