Discovering Biomarkers for Asymptomatic Tuberculosis via Olink Proteomics and Machine Learning

Discovering Biomarkers for Asymptomatic Tuberculosis via Olink Proteomics and Machine Learning

The diagnosis of asymptomatic tuberculosis (TB) remains challenging due to an early disease stage. This study aimed to identify and validate plasma biomarkers for asymptomatic TB by integrating the Olink proteomics with multiple machine learning algorithms. Plasma samples were analyzed using the Oli...

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Bibliographic Details
Main Author: Qingfeng Sun (1924555) (author)
Other Authors: Shanshan Li (114847) (author), Weicong Ren (7504904) (author), You Zhou (129411) (author), Cong Yao (441931) (author), Liuchun Shi (22386779) (author), Aimei Liu (5155967) (author), Mengqiu Gao (502623) (author), Yu Pang (330277) (author)
Published: 2025
Subjects:
Biochemistry
Medicine
Cell Biology
Neuroscience
Sociology
Immunology
Cancer
Infectious Diseases
Virology
Space Science
Biological Sciences not elsewhere classified
Chemical Sciences not elsewhere classified
Information Systems not elsewhere classified
remains challenging due
improving patient outcomes
elisa validation performed
early disease stage
support vector machine
latent tb infection
85 – 0
75 – 0
ltbi ), yielding
asymptomatic tb compared
asymptomatic tb cases
validate plasma biomarkers
asymptomatic tb
plasma samples
machine learning
asymptomatic tuberculosis
discriminative biomarkers
discovering biomarkers
xgboost algorithms
study aimed
significantly upregulated
related proteins
p </
olink proteomics
neural network
high potential
healthy controls
findings indicate
data revealed
analyzed using
05 ).
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