AIMC Topic: Growth Disorders

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Model and variable selection using machine learning methods with applications to childhood stunting in Bangladesh.

Informatics for health & social care Apr 14, 2021
Childhood stunting is a serious public health concern in Bangladesh. Earlier research used conventional statistical methods to identify the risk factors of stunting, and very little is known about the applications and usefulness of machine learning (...
Risk Factors Aged Infant Humans Machine Learning Bangladesh Growth Disorders Child Logistic Models
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Machine learning model demonstrates stunting at birth and systemic inflammatory biomarkers as predictors of subsequent infant growth - a four-year prospective study.

BMC pediatrics Oct 30, 2020
BACKGROUND: Stunting affects up to one-third of the children in low-to-middle income countries (LMICs) and has been correlated with decline in cognitive capacity and vaccine immunogenicity. Early identification of infants at risk is critical for earl...
Growth Disorders Child, Preschool Child Female Infant, Newborn Infant Pakistan Humans Machine Learning Prospective Studies Biomarkers Pregnancy
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Quality of Life in Adolescent Boys with Idiopathic Short Stature: Positive Impact of Growth Hormone and Aromatase Inhibitors.

Hormone research in paediatrics Feb 28, 2019
BACKGROUND: The combination of growth hormone (GH) and aromatase inhibitors (AI) improves linear growth in severely short adolescent boys; however, the effects of this intervention on quality of life (QoL) are unknown. This study assesses whether GH,...
Human Growth Hormone Quality of Life Aromatase Inhibitors Growth Disorders Surveys and Questionnaires Follow-Up Studies Humans Adolescent Male
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Transcriptomics and machine learning predict diagnosis and severity of growth hormone deficiency.

JCI insight Apr 5, 2018
BACKGROUND: The effect of gene expression data on diagnosis remains limited. Here, we show how diagnosis and classification of growth hormone deficiency (GHD) can be achieved from a single blood sample using a combination of transcriptomics and rando...
Adolescent Human Growth Hormone Growth Disorders Child, Preschool Child ROC Curve Gene Expression Profiling Transcriptome Case-Control Studies Female Male Severity of Illness Index Principal Component Analysis Humans Healthy Volunteers Machine Learning Datasets as Topic Biomarkers Gene Regulatory Networks Polymorphism, Single Nucleotide Predictive Value of Tests
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Evaluating Prevalence of Preterm Postnatal Growth Faltering Using Fenton 2013 and INTERGROWTH-21st Growth Charts with Logistic and Machine Learning Models.

Nutrients May 20, 2025
Postnatal growth faltering (PGF) significantly affects premature neonates, leading to compromised neurodevelopment and an increased risk of long-term health complications. This retrospective study at a level III NICU of a tertiary hospital analyzed...
Infant, Newborn Male Prevalence Machine Learning Retrospective Studies Female Gestational Age Infant, Small for Gestational Age Growth Charts Growth Disorders Logistic Models Infant, Premature Humans
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Explainable predictive models of short stature and exploration of related environmental growth factors: a case-control study.

BMC endocrine disorders May 12, 2025
BACKGROUND: Short stature is a prevalent pediatric endocrine disorder for which early detection and prediction are pivotal for improving treatment outcomes. However, existing diagnostic criteria often lack the necessary sensitivity and specificity be...
Case-Control Studies Adolescent Growth Disorders Prognosis Female Male Child, Preschool Child Humans Body Height Machine Learning
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Application of Machine Learning Approaches to Predict Postnatal Growth Failure in Very Low Birth Weight Infants.

Yonsei medical journal Jul 1, 2022
PURPOSE: The aims of the study were to develop and evaluate a machine learning model with which to predict postnatal growth failure (PGF) among very low birth weight (VLBW) infants.
Infant, Newborn Infant Growth Disorders Support Vector Machine Infant, Very Low Birth Weight Humans Machine Learning
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Machine learning-based prediction of response to growth hormone treatment in Turner syndrome: the LG Growth Study.

Journal of pediatric endocrinology & metabolism : JPEM Jan 28, 2020
Background Growth hormone (GH) treatment has become a common practice in Turner syndrome (TS). However, there are only a few studies on the response to GH treatment in TS. The aim of this study is to predict the responsiveness to GH treatment and to ...
Turner Syndrome Child Predictive Value of Tests Humans Body Height Time Factors Machine Learning Growth Disorders Retrospective Studies Female Male Human Growth Hormone
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