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Growth Hormone Treatment Response and Machine Learning-Based Prediction in Idiopathic GHD and ISS: Analysis of the Korean LG Growth Study
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DOI：10.1111/cen.70163.png)
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Abstract
En 中文
Individual responses to recombinant human growth hormone (rhGH) therapy vary widely among children with idiopathic growth hormone deficiency (iGHD) and idiopathic short stature (ISS), making accurate prediction of treatment outcomes clinically important. This study aimed to develop and compare machine learning (ML)-based and conventional statistical models to predict short-term growth response and mid-parental height (MPH) attainment following rhGH therapy in iGHD and ISS patients.
Keywords:
Machine Learning
Growth Hormone Therapy
Idiopathic Growth Hormone Deficiency
Idiopathic Short Stature
Predictive Modeling
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