Design and Implementation of a Medical Question and Answer System Based on Deep Learning. (21st September 2022)
- Record Type:
- Journal Article
- Title:
- Design and Implementation of a Medical Question and Answer System Based on Deep Learning. (21st September 2022)
- Main Title:
- Design and Implementation of a Medical Question and Answer System Based on Deep Learning
- Authors:
- Hu, Yun
Han, Guokai
Liu, Xintang
Li, Hui
Xing, Libao
Gu, Yong
Zhou, Zuojian
Li, Haining - Other Names:
- Li Lianhui Academic Editor.
- Abstract:
- Abstract : Medical services play a pivotal role in people's lives and in the national economy. Although the number of healthcare facilities is currently growing every year, there are still major problems in terms of access and pressure on the flow of people. Therefore, there is an urgent need for complementary medical services to alleviate the flow of patients and their psychological burden and to enable them to receive timely medical advice. This article designs and implements a medical Q&A system based on deep learning. We took a retrieval-based approach, using crawler technology that has been manually reviewed to build the Q&A database, and the Seq2Seq algorithm and the TF-IDF model to build the answer generation model. The medical question and answer system developed enable effective Q&A and relevant medical advice to be given. The algorithm proposed in this paper can quickly provide users with accurate answers compared to conventional search methods in real datasets.
- Is Part Of:
- Mathematical problems in engineering. Volume 2022(2022)
- Journal:
- Mathematical problems in engineering
- Issue:
- Volume 2022(2022)
- Issue Display:
- Volume 2022, Issue 2022 (2022)
- Year:
- 2022
- Volume:
- 2022
- Issue:
- 2022
- Issue Sort Value:
- 2022-2022-2022-0000
- Page Start:
- Page End:
- Publication Date:
- 2022-09-21
- Subjects:
- Engineering mathematics -- Periodicals
510.2462 - Journal URLs:
- https://www.hindawi.com/journals/mpe/ ↗
http://www.gbhap-us.com/journals/238/238-top.htm ↗ - DOI:
- 10.1155/2022/4600404 ↗
- Languages:
- English
- ISSNs:
- 1024-123X
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD Digital store
- Ingest File:
- 24060.xml