Prediction of Large for Gestational Age Infants in Overweight and Obese Women at Approximately 20 Gestational Weeks

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Title: Prediction of Large for Gestational Age Infants in Overweight and Obese Women at Approximately 20 Gestational Weeks
Authors: Du, YuhanMehegan, JohnMcAuliffe, Fionnuala M.Mooney, Catherine
Permanent link: http://hdl.handle.net/10197/12183
Date: 24-Sep-2020
Online since: 2021-05-20T08:40:13Z
Abstract: Large for gestational age (LGA) births are associated with many maternal and perinatal complications. As overweight and obesity are risk factors for LGA, we aimed to predict LGA in overweight and obese women at approximately 20 gestational weeks, so that we can identify women at risk of LGA early to allow for appropriate interventions. A random forest algorithm was applied to maternal characteristics and blood biomarkers at baseline and 20 gestational weeks' ultrasound scan findings to develop a prediction model. Here we present our preliminary results demonstrating potential for use in clinical decision support for identifying patients early in pregnancy at risk of an LGA birth.
Type of material: Conference Publication
Publisher: ACM
Copyright (published version): 2020 the Authors
Keywords: Health informaticsInfant birth weightPrediction models
DOI: 10.1145/3388440.3414906
Other versions: http://acm-bcb.org/2020/index.php
Language: en
Status of Item: Peer reviewed
Is part of: BCB '20: Proceedings of the 11th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics
Conference Details: The 11th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM-BCB), Virtual Conference, 21-24 September 2020
ISBN: 9781450379649
This item is made available under a Creative Commons License: https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
Appears in Collections:Computer Science Research Collection

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