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

Decision Support for Health Professionals (1210) Machine Learning (1501) Ontologies, Classifications, and Coding (243)

Published on in Vol 7, No 3 (2019): Jul-Sep

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/13562, first published .
Identification of Knee Osteoarthritis Based on Bayesian Network: Pilot Study

Identification of Knee Osteoarthritis Based on Bayesian Network: Pilot Study

Identification of Knee Osteoarthritis Based on Bayesian Network: Pilot Study

Authors of this article:

Bo Sheng1, 2 Author Orcid Image ;   Liang Huang3 Author Orcid Image ;   Xiangbin Wang1 Author Orcid Image ;   Jie Zhuang4 Author Orcid Image ;   Lihua Tang2 Author Orcid Image ;   Chao Deng5 Author Orcid Image ;   Yanxin Zhang1, 3, 4 Author Orcid Image
Article Authors Cited by (7) Tweetations (6) Metrics

Journals

  1. Sheng B, Wang X, Hou M, Huang J, Xiong S, Zhang Y. An automated system for motor function assessment in stroke patients using motion sensing technology: A pilot study. Measurement 2020;161:107896 View
  2. Fan Z, Wang C, Fang L, Ma L, Niu T, Wang Z, Lu J, Yuan B, Liu G. Risk factors and a Bayesian network model to predict ischemic stroke in patients with dilated cardiomyopathy. Frontiers in Neuroscience 2022;16 View
  3. Sheng B, Zhao J, Tao J, Zhang Y, Duan C, Zhuang J. Smart fall prediction paradigm for community-dwelling seniors through fitness screening protocols and machine learning. Measurement 2022;200:111584 View
  4. McCabe P, Lisboa P, Baltzopoulos B, Olier I, Cowley H. Externally validated models for first diagnosis and risk of progression of knee osteoarthritis. PLOS ONE 2022;17(7):e0270652 View
  5. Hill A, Joyner C, Keith-Jopp C, Yet B, Tuncer Sakar C, Marsh W, Morrissey D. Assessing Serious Spinal Pathology Using Bayesian Network Decision Support: Development and Validation Study. JMIR Formative Research 2023;7:e44187 View
  6. Lee D, Han H, Ro D, Lee Y. Development of the machine learning model that is highly validated and easily applicable to predict radiographic knee osteoarthritis progression. Journal of Orthopaedic Research 2025;43(1):128 View
  7. Malathi S, Bharamagoudar G, Shiragudikar S. Diagnosing and grading knee osteoarthritis from X-ray images using deep neural angular extreme learning machine. Proceedings of the Indian National Science Academy 2024 View