DATLMedQA: A Data Augmentation and Transfer Learning Based Solution for Medical Question Answering
With the outbreak of COVID-19 that has prompted an increased focus on self-care, more and more people hope to obtain disease knowledge from the Internet. In response to this demand, medical question answering and question generation tasks have become an important part of natural language processing...
Main Authors: | Shuohua Zhou, Yanping Zhang |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2021-11-01
|
Series: | Applied Sciences |
Subjects: | |
Online Access: | https://www.mdpi.com/2076-3417/11/23/11251 |
Similar Items
-
Enhancement of Question Answering System Accuracy via Transfer Learning and BERT
by: Kai Duan, et al.
Published: (2022-11-01) -
Answer Category-Aware Answer Selection for Question Answering
by: Weijing Wu, et al.
Published: (2021-01-01) -
Arabic Narrative Question Answering (QA) Using Transformer Models
by: Mohammad A. Ateeq, et al.
Published: (2024-01-01) -
Standard refrigeration and air conditioning : questions and answers/
by: 247465 Elonka, Stephen Michael, et al.
Published: (1973) -
ComQA: Question Answering Over Knowledge Base via Semantic Matching
by: Hai Jin, et al.
Published: (2019-01-01)