Machine learning improves early prediction of small-for-gestational-age births and reveals nuchal fold thickness as unexpected predictor

10.1002/pd.5903

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Bibliographic Details
Main Authors: Saw, Shier Nee, Biswas, Arijit, Mattar, Citra Nurfarah Zaini, Lee, Hwee Kuan, Yap, Choon Hwai
Other Authors: BIOMEDICAL ENGINEERING
Format: Article
Published: John Wiley and Sons Ltd 2022
Online Access:https://scholarbank.nus.edu.sg/handle/10635/232240
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spelling sg-nus-scholar.10635-2322402024-04-17T08:55:35Z Machine learning improves early prediction of small-for-gestational-age births and reveals nuchal fold thickness as unexpected predictor Saw, Shier Nee Biswas, Arijit Mattar, Citra Nurfarah Zaini Lee, Hwee Kuan Yap, Choon Hwai BIOMEDICAL ENGINEERING OBSTETRICS & GYNAECOLOGY DEPARTMENT OF COMPUTER SCIENCE 10.1002/pd.5903 Prenatal Diagnosis 41 4 505-516 2022-10-11T08:09:41Z 2022-10-11T08:09:41Z 2021-02-12 Article Saw, Shier Nee, Biswas, Arijit, Mattar, Citra Nurfarah Zaini, Lee, Hwee Kuan, Yap, Choon Hwai (2021-02-12). Machine learning improves early prediction of small-for-gestational-age births and reveals nuchal fold thickness as unexpected predictor. Prenatal Diagnosis 41 (4) : 505-516. ScholarBank@NUS Repository. https://doi.org/10.1002/pd.5903 0197-3851 https://scholarbank.nus.edu.sg/handle/10635/232240 Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/ John Wiley and Sons Ltd Scopus OA2021
institution National University of Singapore
building NUS Library
continent Asia
country Singapore
Singapore
content_provider NUS Library
collection ScholarBank@NUS
description 10.1002/pd.5903
author2 BIOMEDICAL ENGINEERING
author_facet BIOMEDICAL ENGINEERING
Saw, Shier Nee
Biswas, Arijit
Mattar, Citra Nurfarah Zaini
Lee, Hwee Kuan
Yap, Choon Hwai
format Article
author Saw, Shier Nee
Biswas, Arijit
Mattar, Citra Nurfarah Zaini
Lee, Hwee Kuan
Yap, Choon Hwai
spellingShingle Saw, Shier Nee
Biswas, Arijit
Mattar, Citra Nurfarah Zaini
Lee, Hwee Kuan
Yap, Choon Hwai
Machine learning improves early prediction of small-for-gestational-age births and reveals nuchal fold thickness as unexpected predictor
author_sort Saw, Shier Nee
title Machine learning improves early prediction of small-for-gestational-age births and reveals nuchal fold thickness as unexpected predictor
title_short Machine learning improves early prediction of small-for-gestational-age births and reveals nuchal fold thickness as unexpected predictor
title_full Machine learning improves early prediction of small-for-gestational-age births and reveals nuchal fold thickness as unexpected predictor
title_fullStr Machine learning improves early prediction of small-for-gestational-age births and reveals nuchal fold thickness as unexpected predictor
title_full_unstemmed Machine learning improves early prediction of small-for-gestational-age births and reveals nuchal fold thickness as unexpected predictor
title_sort machine learning improves early prediction of small-for-gestational-age births and reveals nuchal fold thickness as unexpected predictor
publisher John Wiley and Sons Ltd
publishDate 2022
url https://scholarbank.nus.edu.sg/handle/10635/232240
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