The DOI matches its Crossref record; 48 of the 48 references it cites were found in a registry or an index.
CNN-RNN Based Intelligent Recommendation for Online Medical Pre-Diagnosis Support
Abstract
The rapidly developed Health 2.0 technology has provided people with more opportunities to conduct online medical consultation than ever before. Understanding contexts within different online medical communications and activities becomes a significant issue to facilitate patients' medical decision making process. As a subcategory of machine learning, neural networks have drawn increasing attentions in natural language processing applications. In this article, we focus on modeling and analyzing the patient-physician-generated data based on an integrated CNN-RNN framework, in order to deal with the situation that patients' online inquiries are usually not very long. A so-called DP-CRNN algorithm is developed with a newly designed neural network structure, to extract and highlight the combination of semantic and sequential features in terms of patient's inquiries. An intelligent recommendation method is then proposed to provide patients with automatic clinic guidance and pre-diagnosis suggestions, in which a clustering mechanism is utilized to refine the learning process with more precise diagnosis scope and more representative features. Experiments based on the collected real world data demonstrate the effectiveness of our proposed model and method for intelligent pre-diagnosis service in online medical environments.
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Cited by
Federated Learning Empowered Real-Time Medical Data Processing Method for Smart Healthcare
Guo, K., Chen, T., Ren, S., Li, N., Hu, M., & Kang, J. (2024) · IEEE/ACM Transactions on Computational Biology and Bioinformatics · doi:10.1109/tcbb.2022.3185395 · Cited by 63
DFML: Dynamic Federated Meta-Learning for Rare Disease Prediction
Chen, B., Chen, T., Zeng, X., Zhang, W., Lu, Q., Hou, Z., Zhou, J., & Helal, S. (2024) · IEEE/ACM Transactions on Computational Biology and Bioinformatics · doi:10.1109/tcbb.2023.3239848 · Cited by 31
Metadata
- Authors
- Zhou, X., Li, Y., & Liang, W.
- Venue
- IEEE/ACM Transactions on Computational Biology and Bioinformatics
- Published
- 2021-05-01
- Volume
- 18
- Issue
- 3
- Pages
- 912-921
- ISSN
- 1545-5963 (ISSN-L)
- 1557-9964
- 2374-0043
- OpenAlex
- W3024836211
- Cited by
- 455
- References
- 48
- FWCI
- 73.92
- Type
- journal article
- Language
- en
- Open access
- closed
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