Identifying discriminative features for diagnosis of Kashin-Beck disease among adolescents.
Introduction: Diagnosing Kashin-Beck disease (KBD) involves damages to multiple joints and carries variable clinical symptoms, posing great challenge to the diagnosis of KBD for clinical practitioners. However, it is still unclear which clinical features of KBD are more informative for the diagnosis...
| Publicado en: | BMC Musculoskeletal Disorders Vol. 22; no. 1; pp. 1 - 11 |
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| Autores principales: | , , , , , , , , , , , |
| Formato: | Journal Article |
| Publicado: |
BioMed Central
9/18/2021
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=152519341&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 152519341 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 14712474 1CI5 jtl: BMC Musculoskeletal Disorders issn: 14712474 maglogo: N pubinfo: dt: 9/18/2021 vid: 22 iid: 1 pid: 24147 pub: BioMed Central artinfo: ui: 152519341 152519341 NLM34537022 10.1186/s12891-021-04514-z NLM34537022 152519341 ppf: 1 ppct: 10 formats: tig: atl: Identifying discriminative features for diagnosis of Kashin-Beck disease among adolescents. aug: au: Zhang, Yanan Wei, Xiaoli Cao, Chunxia Yu, Fangfang Li, Wenrong Zhao, Guanghui Wei, Haiyan Zhang, Feng'e Meng, Peilin Sun, Shiquan Lammi, Mikko Juhani Guo, Xiong affil: School of Public Health, Xi'an Jiaotong University, Key Laboratory of Trace Elements and Endemic Diseases, National Health Commission of the People's Republic of China, Xi'an, Shaanxi, P.R. China sug: subj: Osteochondrodysplasias Fingers Osteochondrodysplasias Epidemiology Hand Joints Finger Joint Adolescence Range of Motion Clinical Assessment Tools Scales Psychological Tests Adolescent: 13-18 years ab: Introduction: Diagnosing Kashin-Beck disease (KBD) involves damages to multiple joints and carries variable clinical symptoms, posing great challenge to the diagnosis of KBD for clinical practitioners. However, it is still unclear which clinical features of KBD are more informative for the diagnosis of Kashin-Beck disease among adolescent.Methods: We first manually extracted 26 possible features including clinical manifestations, and pathological changes of X-ray images from 400 KBD and 400 non-KBD adolescents. With such features, we performed four classification methods, i.e., random forest algorithms (RFA), artificial neural networks (ANNs), support vector machines (SVMs) and linear regression (LR) with four feature selection methods, i.e., RFA, minimum redundancy maximum relevance (mRMR), support vector machine recursive feature elimination (SVM-RFE) and Relief. The performance of diagnosis of KBD with respect to different classification models were evaluated by sensitivity, specificity, accuracy, and the area under the receiver operating characteristic (ROC) curve (AUC).Results: Our results demonstrated that the 10 out of 26 discriminative features were displayed more powerful performance, regardless of the chosen of classification models and feature selection methods. These ten discriminative features were distal end of phalanges alterations, metaphysis alterations and carpals alterations and clinical manifestations of ankle joint movement limitation, enlarged finger joints, flexion of the distal part of fingers, elbow joint movement limitation, squatting limitation, deformed finger joints, wrist joint movement limitation.Conclusions: The selected ten discriminative features could provide a fast, effective diagnostic standard for KBD adolescents. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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