Prediction of preterm birth based on machine learning using bacterial risk score in cervicovaginal fluid,American Journal of Reproductive Immunology

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Prediction of preterm birth based on machine learning using bacterial risk score in cervicovaginal fluid
American Journal of Reproductive Immunology ( IF 2.5 ) Pub Date : 2021-04-27 , DOI: 10.1111/aji.13435
Sunwha Park ₁ , Daejoong Oh ₂ , Hanna Heo ₁ , Gain Lee _{1,

3} , Soo Min Kim _{1,

3} , AbuZar Ansari ₁ , Young-Ah You ₁ , Yun Ji Jung ₄ , Young-Han Kim ₄ , Myunghoon Lee ₂ , Young Ju Kim _{1,

3}

Affiliation

Preterm birth (PTB) is a major cause of increased morbidity and mortality in newborns. The main cause of spontaneous PTB (sPTB) is the activation of an inflammatory response as a result of ascending genital tract infection. Despite various studies on the effects of the vaginal microbiome on PTB, a practical method for its clinical application has yet to be developed.

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