Predicting Low Cognitive Ability at Age 5-Feature Selection Using Machine Learning Methods and Birth Cohort Data.
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ABSTRACT:
SUBMITTER: Bowe AK
PROVIDER: S-EPMC9684182 | biostudies-literature | 2022
REPOSITORIES: biostudies-literature
Publications
Predicting Low Cognitive Ability at Age 5-Feature Selection Using Machine Learning Methods and Birth Cohort Data.
Bowe Andrea K AK Lightbody Gordon G Staines Anthony A Kiely Mairead E ME McCarthy Fergus P FP Murray Deirdre M DM
International journal of public health 20221110
<b>Objectives:</b> In this study, we applied the random forest (RF) algorithm to birth-cohort data to train a model to predict low cognitive ability at 5 years of age and to identify the important predictive features. <b>Methods:</b> Data was from 1,070 participants in the Irish population-based BASELINE cohort. A RF model was trained to predict an intelligence quotient (IQ) score ≤90 at age 5 years using maternal, infant, and sociodemographic features. Feature importance was examined and intern ...[more]
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