Online Doctor Recommendation with Convolutional Neural Network and Sparse Inputs
Joint Authors
Yan, Yongjie
Yu, Guang
Yan, Xiangbin
Source
Computational Intelligence and Neuroscience
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-10-15
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
The recommendation system in the online medical consultation website is a system to assist patients to find appropriate doctors.
Based on the analysis of the current situation of the development of an online medical community (Haodf.com) in China, this paper puts forward recommendation suggestions of finding the right hospital and doctor to promote the rapid integration of Internet technology and traditional medical services.
A new recommendation model called Probabilistic Matrix Factorization integrated with Convolutional Neural Network (PMF-CNN) is proposed in the paper.
Doctors’ data in Haodf.com were used to evaluate the performance of our system.
The model improves the performance of medical consultation recommendations by fusing review text and doctor information based on CNN (Convolutional Neural Network).
Specifically, CNN is used to learn the feature representation of the review text and the doctors’ information.
Furthermore, the extended matrix factorization model is exploited to fuse the review information feature and the initial value of the doctors’ information for recommendation.
As is shown in the experimental results on Haodf.com datasets, the proposed PMF-CNN achieves better recommendation performances than the other state-of-the-art recommendation algorithms.
And the recommendation system in an online medical website improves the utilization efficiency of doctors and the balance of public health resources allocation.
American Psychological Association (APA)
Yan, Yongjie& Yu, Guang& Yan, Xiangbin. 2020. Online Doctor Recommendation with Convolutional Neural Network and Sparse Inputs. Computational Intelligence and Neuroscience،Vol. 2020, no. 2020, pp.1-10.
https://search.emarefa.net/detail/BIM-1138864
Modern Language Association (MLA)
Yan, Yongjie…[et al.]. Online Doctor Recommendation with Convolutional Neural Network and Sparse Inputs. Computational Intelligence and Neuroscience No. 2020 (2020), pp.1-10.
https://search.emarefa.net/detail/BIM-1138864
American Medical Association (AMA)
Yan, Yongjie& Yu, Guang& Yan, Xiangbin. Online Doctor Recommendation with Convolutional Neural Network and Sparse Inputs. Computational Intelligence and Neuroscience. 2020. Vol. 2020, no. 2020, pp.1-10.
https://search.emarefa.net/detail/BIM-1138864
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1138864