Development and validation of a diagnostic model to differentiate spinal tuberculosis from pyogenic spondylitis by combining multiple machine learning algorithms

Development and validation of a diagnostic model to differentiate spinal tuberculosis from pyogenic spondylitis by combining multiple machine learning algorithms

This study focused on the development and validation of a diagnostic model to differentiate between spinal tuberculosis (STB) and pyogenic spondylitis (PS). We analyzed a total of 387 confirmed cases, out of which 241 were diagnosed with STB and 146 were diagnosed with PS. These cases were randomly...

Full description

Bibliographic Details
Main Authors: Chengqian Huang, Jing Zhuo, Chong Liu, Shaofeng Wu, Jichong Zhu, Tianyou Chen, Bin Zhang, Sitan Feng, Chenxing Zhou, Zequn Wang, Shengsheng Huang, Liyi Chen, Xinli Zhan
Format: Article
Language:English
Published: Association of Basic Medical Sciences of Federation of Bosnia and Herzegovina 2024-03-01
Series:Biomolecules & Biomedicine
Subjects:
Spinal tuberculosis (STB)
pyogenic spondylitis (PS)
machine learning (ML)
diagnostic model
nomogram
Online Access:https://www.bjbms.org/ojs/index.php/bjbms/article/view/9663

Internet

https://www.bjbms.org/ojs/index.php/bjbms/article/view/9663

Similar Items