Features selection from the literature of potentials risk factors of preterm birth.

Khan, Wasif; Zaki, Nazar; Ghenimi, Nadirah; Ahmad, Amir; Bian, Jiang; Masud, Mohammad M.; Ali, Nasloon; Govender, Romona; Ahmed, Luai A.

doi:10.1371/journal.pone.0293925.s001

pone.0293925.s001.docx (28.56 kB)

Features selection from the literature of potentials risk factors of preterm birth.

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posted on 2023-12-27, 18:27 authored by Wasif Khan, Nazar Zaki, Nadirah Ghenimi, Amir Ahmad, Jiang Bian, Mohammad M. Masud, Nasloon Ali, Romona Govender, Luai A. Ahmed

Features selection from the literature of potentials risk factors of preterm birth.

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xgboost model exhibited valuable screening tool united arab emirates shapley additive explanations providing appropriate care provide comprehensive explanations provide appropriate care operator receiving curves local interpretable model individual patient analysis body mass index artificial intelligence literature relevant risk factors previous cesarean section existing models hinders agnostic explanation algorithms 3509 pregnant women predicting ptb within study holds promise six ml algorithms shown promise risk factor previous ptb existing medical study analyzed study aimed term morbidities specific population significant perinatal reduce morbidity ptb prediction ptb based prospective cohort predict ptb performed using overall incidence often leading mortality related maternal age machine learning lime analyses lime ).individualized impact complex challenge clinical utility best performance assist clinicians amniotic infection &# 8220

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Features selection from the literature of potentials risk factors of preterm birth.

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