A Machine Learning-Based Analytic Pipeline Applied to Clinical and Serum IgG Immunoproteome Data To Predict Chlamydia trachomatis Genital Tract Ascension and Incident Infection in Women

We developed a reusable and open-source machine learning (ML) pipeline that can provide an analytical framework for rigorous biomarker discovery. We implemented the ML pipeline to determine the predictive potential of clinical and immunoproteome antibody data for outcomes associated with Chlamydia t...

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Detalles Bibliográficos
Autores principales: Liu, Chuwen, Mokashi, Neha Vivek, Darville, Toni, Sun, Xuejun, O’Connell, Catherine M., Hufnagel, Katrin, Waterboer, Tim, Zheng, Xiaojing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Society for Microbiology 2023
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10434056/
https://www.ncbi.nlm.nih.gov/pubmed/37318345
http://dx.doi.org/10.1128/spectrum.04689-22

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10434056/
https://www.ncbi.nlm.nih.gov/pubmed/37318345
http://dx.doi.org/10.1128/spectrum.04689-22

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