This paper is in the following e-collection/theme issue:

Theme issue 2019: Health Natural Language Processing (17) Clinical Information and Decision Making (1407) Complementary and Alternative Medicine (29) Machine Learning (1465) Natural Language Processing (693)

Published on in Vol 8, No 6 (2020): June

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/17608, first published .
Artificial Intelligence–Based Traditional Chinese Medicine Assistive Diagnostic System: Validation Study

Artificial Intelligence–Based Traditional Chinese Medicine Assistive Diagnostic System: Validation Study

Artificial Intelligence–Based Traditional Chinese Medicine Assistive Diagnostic System: Validation Study

Authors of this article:

Hong Zhang1 Author Orcid Image ;   Wandong Ni2 Author Orcid Image ;   Jing Li1 Author Orcid Image ;   Jiajun Zhang3 Author Orcid Image
Article Authors Cited by (45) Tweetations (2) Metrics

Journals

  1. Shin D, Lee K, Adeluwa T, Hur J. Machine Learning-Based Predictive Modeling of Postpartum Depression. Journal of Clinical Medicine 2020;9(9):2899 View
  2. Zhao Z, Wu C, Zhang S, He F, Liu F, Wang B, Huang Y, Shi W, Jian D, Xie H, Yeh C, Li J. A Novel Convolutional Neural Network for the Diagnosis and Classification of Rosacea: Usability Study. JMIR Medical Informatics 2021;9(3):e23415 View
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  19. Ren G, Yu K, Xie Z, Liu L, Wang P, Zhang W, Wang Y, Wu X. Differentiation of lumbar disc herniation and lumbar spinal stenosis using natural language processing–based machine learning based on positive symptoms. Neurosurgical Focus 2022;52(4):E7 View
  20. Li N, Yu J, Mao X, Zhao Y, Huang L, Gu J. The Research and Development Thinking on the Status of Artificial Intelligence in Traditional Chinese Medicine. Evidence-Based Complementary and Alternative Medicine 2022;2022:1 View
  21. Gong L. Ml-Prdf：A Syndrome Differentiation Model of Traditional Chinese Medicine Based on Pcc-Mlrf and Multi-Label Deep Forest. SSRN Electronic Journal 2022 View
  22. Ma S, Liu J, Li W, Liu Y, Hui X, Qu P, Jiang Z, Li J, Wang J. Machine learning in TCM with natural products and molecules: current status and future perspectives. Chinese Medicine 2023;18(1) View
  23. Xi C, Zhang J, Xiao Y, Liu J, Liu W, Tian D, Liu Y, Zhai S, Ye H. Research on Application Paradigm of Random Sampling Method in Data Analysis of Traditional Chinese Medicine—Taking Insomnia Prescriptions of Famous Old Tcm Physicians as an Example. SSRN Electronic Journal 2022 View
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  25. Yang X, Ding C. SMRGAT: A traditional Chinese herb recommendation model based on a multi-graph residual attention network and semantic knowledge fusion. Journal of Ethnopharmacology 2023;315:116693 View
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  30. Li W, Ge X, Liu S, Xu L, Zhai X, Yu L. Opportunities and challenges of traditional Chinese medicine doctors in the era of artificial intelligence. Frontiers in Medicine 2024;10 View
  31. Tian D, Chen W, Xu D, Xu L, Xu G, Guo Y, Yao Y. A review of traditional Chinese medicine diagnosis using machine learning: Inspection, auscultation-olfaction, inquiry, and palpation. Computers in Biology and Medicine 2024;170:108074 View
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  36. Madanay F, Tu K, Campagna A, Davis J, Doerstling S, Chen F, Ubel P. Classification of Patients’ Judgments of Their Physicians in Web-Based Written Reviews Using Natural Language Processing: Algorithm Development and Validation. Journal of Medical Internet Research 2024;26:e50236 View
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