PTBD: a machine learning-based non-invasive diagnostic model for pulmonary tuberculosis using large-scale blood transcriptomes

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Authors

Changchun Wu · University of Electronic Science and Technology of China

Xuejun Xie · University of Electronic Science and Technology of China

Zixin Huang · University of Electronic Science and Technology of China

Yuwei Zhou · University of Electronic Science and Technology of China

Yushu Gou · University of Electronic Science and Technology of China

Mengze Du · Chengdu University of Technology

Abstract

This study provides a broadly applicable tool for early PTB diagnosis, facilitating timely intervention and potentially reducing global PTB burden. Moreover, PTBD uncovers novel transcriptomic biomarkers, represented by five diagnostic gene-pair expression patterns that embody the molecular hallmarks of PTB.

Topics & Keywords

Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis Lung Cancer Treatments and Mutations RNA modifications and cancer

UN Sustainable Development Goals

Good health and well-being

Publication Details

Published in: BMC Biology

DOI: 10.1186/s12915-026-02585-9

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