2021
DOI: 10.3389/fped.2021.694958
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Nomogram for Predicting Bone Development State of Female Children and Adolescents–A Fast Screening Approach Based on Pubes Stages for Growth and Development

Abstract: Objective: To develop a nomogram for predicting bone development state (BDS) of female children and adolescents in a large scale.Methods: Four hundred forty-seven female students were designated as the training cohort to develop the predictive model, whereas 196 female students were used as the validation cohort to verify the established model. Bone age, height, body mass, body fat percentage, and secondary sexual characteristics were recorded, and BDS was determined with the chronological age and bone age. Mu… Show more

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Cited by 3 publications
(2 citation statements)
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References 26 publications
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“…It can detect more trace metabolites and find some significantly changed trace metabolites, which are difficult to find changes by traditional methods ( Heaney et al, 2019 ; Schranner et al, 2020 ). In this study, the AUC value of the evaluation model established by using the changes of trace metabolites of human serum and athletes’ physical characteristics was greatly improved, reaching more than 0.9, which has obvious advantages compared with the 0.7 level of the evaluation model with other methods ( Yang et al, 2021a ; 2021b ). Besides, there are still some limitations in this study.…”
Section: Discussionmentioning
confidence: 84%
“…It can detect more trace metabolites and find some significantly changed trace metabolites, which are difficult to find changes by traditional methods ( Heaney et al, 2019 ; Schranner et al, 2020 ). In this study, the AUC value of the evaluation model established by using the changes of trace metabolites of human serum and athletes’ physical characteristics was greatly improved, reaching more than 0.9, which has obvious advantages compared with the 0.7 level of the evaluation model with other methods ( Yang et al, 2021a ; 2021b ). Besides, there are still some limitations in this study.…”
Section: Discussionmentioning
confidence: 84%
“…In the context of talent evaluation, keyword extraction involves the use of advanced natural language processing techniques to automatically identify and extract relevant keywords, phrases, and concepts from the textual data associated with a candidate's profile. The textual data can include a candidate's resume, cover letter, project descriptions, blog posts, social media content, and any other written material that provides insights into their professional background and expertise [14]. These texts are parsed and analyzed to identify and prioritize the most significant words and phrases that represent the candidate's skills, experience, and domain knowledge.…”
Section: Introductionmentioning
confidence: 99%