1 code implementation • NAACL (NLPMC) 2021 • Khalil Mrini, Franck Dernoncourt, Walter Chang, Emilia Farcas, Ndapa Nakashole
Understanding the intent of medical questions asked by patients, or Consumer Health Questions, is an essential skill for medical Conversational AI systems.
no code implementations • NAACL (BioNLP) 2021 • Khalil Mrini, Franck Dernoncourt, Seunghyun Yoon, Trung Bui, Walter Chang, Emilia Farcas, Ndapa Nakashole
We show that both transfer learning methods combined achieve the highest ROUGE scores.
1 code implementation • COLING 2022 • Khalil Mrini, Harpreet Singh, Franck Dernoncourt, Seunghyun Yoon, Trung Bui, Walter Chang, Emilia Farcas, Ndapa Nakashole
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.
no code implementations • ACL 2021 • Khalil Mrini, Emilia Farcas, Ndapa Nakashole
The recursive nature of our model is able to represent all levels of syntactic parse trees with only one additional self-attention layer.
1 code implementation • ACL 2021 • Khalil Mrini, Franck Dernoncourt, Seunghyun Yoon, Trung Bui, Walter Chang, Emilia Farcas, Ndapa Nakashole
Users of medical question answering systems often submit long and detailed questions, making it hard to achieve high recall in answer retrieval.