Development of diagnostic algorithm using machine learning for distinguishing between active tuberculosis and latent tuberculosis infection

Development of diagnostic algorithm using machine learning for distinguishing between active tuberculosis and latent tuberculosis infection

Highlights The first study to establish 28 models using machine learning for TB diagnosis. The first TB diagnostic model based on routine, TB-specific and non-specific tests. Cforest model presented excellent performance in discriminating ATB from LTBI.

Bibliographic Details
Main Authors: Ying Luo, Ying Xue, Wei Liu, Huijuan Song, Yi Huang, Guoxing Tang, Feng Wang, Qi Wang, Yimin Cai, Ziyong Sun
Format: Article
Language:English
Published: BMC 2022-12-01
Series:BMC Infectious Diseases
Subjects:
Diagnostic algorithm
Machine learning
Active tuberculosis
Latent tuberculosis infection
Discrimination
Online Access:https://doi.org/10.1186/s12879-022-07954-7

Internet

https://doi.org/10.1186/s12879-022-07954-7

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