成骨不全
人类遗传学
计算机科学
生物信息学
机器学习
人工智能
医学
计算生物学
生物
遗传学
解剖
基因
作者
Hongjiang Yang,Wenbiao Zhu,Bo Li,Hao Wang,Cong Xing,Xiong Yang,Xiuzhi Ren,Guangzhi Ning
标识
DOI:10.1186/s13023-024-03433-1
摘要
Osteogenesis imperfecta (OI) is a genetic disorder characterized by low bone mass, bone fragility and short stature. There is a significant gap in knowledge regarding the growth patterns across different types of OI, and the prediction of height in individuals with OI was not adequately addressed. In this study, we described the growth patterns and predicted the height of individuals with OI employing multiple machine learning (ML) models. Accurate height prediction enables effective monitoring and facilitates the development of personalized intervention plans for managing OI.
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