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

Decision Support for Health Professionals (919) Machine Learning (1185) Ontologies, Classifications, and Coding (177)

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 Sheng 1, 2 Author Orcid Image ;   Liang Huang 3 Author Orcid Image ;   Xiangbin Wang 2 Author Orcid Image ;   Jie Zhuang 4 Author Orcid Image ;   Lihua Tang 1 Author Orcid Image ;   Chao Deng 5 Author Orcid Image ;   Yanxin Zhang 2, 3, 4 Author Orcid Image
Article Authors Cited by (5) 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