Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6865723 | Neurocomputing | 2015 | 6 Pages |
Abstract
The traditional diagnosis method of cervical spondylosis is based on X-ray reading. However, some divergences often take place on the type classification for there exist some deficiencies in the definition of the X-ray, the experience of clinicians in X-ray reading and clinic work and so on. To cope with the matter, we put forward a method based on maximum likelihood theory to solve the type classification of cervical spondylosis in the article. We firstly establish the X-ray quantitative diagnosis model according to analysis of 1034 clinical cases, and then carry it out with 60 cases of the test group. Although there is no statistically significant difference in the rate of diagnosis, slightly higher is observed in the aspect of accuracy when comparing the maximum likelihood method with a X-ray reading method 80.0% vs 68.3%, so the maximum likelihood method based on X-ray quantitative diagnosis is an efficient approach in the type classification of cervical spondylosis.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Xinghu Yu, Ming Liu, Lingzhi Meng, Liangbi Xiang,