Medical Diagnosis of Cerebral Palsy Rehabilitation Using Eye Images in Machine Learning Techniques.
Cerebral Palsy (CP) is a non progressive neurological disorders commonly associated with a spectrum of developmental disabilities such as strabismus (misalignment of eye). The Eye image are captured through camera, this make the quick diagnosis and examination the periodical assessment for CP kids....
| Publicado en: | Journal of Medical Systems Vol. 43; no. 8 |
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| Autores principales: | , , |
| Formato: | equations & formulas pictorial research tables/charts Journal Article |
| Publicado: |
Springer Nature
Aug2019
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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=137490066&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 137490066 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01485598 4N0 jtl: Journal of Medical Systems issn: 01485598 maglogo: N pubinfo: dt: Aug2019 vid: 43 iid: 8 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 137490066 137490066 137490066 10.1007/s10916-019-1410-6 137490066 ppct: 1 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Medical Diagnosis of Cerebral Palsy Rehabilitation Using Eye Images in Machine Learning Techniques. aug: au: Illavarason, P. Arokia Renjit, J. Mohan Kumar, P. affil: Faculty of Information and Communication Engineering, CEG, Anna University, Chennai, India sug: subj: Cerebral Palsy Diagnosis Diagnostic Imaging Machine Learning Image Processing, Computer Assisted Human Strabismus Diagnosis Nystagmus, Pathologic Diagnosis Algorithms Child, Preschool Child Eye Movements Developmental Disabilities Child, Preschool: 2-5 years Child: 6-12 years ab: Cerebral Palsy (CP) is a non progressive neurological disorders commonly associated with a spectrum of developmental disabilities such as strabismus (misalignment of eye). The Eye image are captured through camera, this make the quick diagnosis and examination the periodical assessment for CP kids. By capturing the Eye Movement of 40 children with CP (aged 3–11 years) with relatively mild motor-impairment and also we have analyzed the performance of CP children periodically. Nowadays, Bio-Medical image processing and Machine learning Classification algorithm used for detection and diagnosis the certain diseases and plays the important tool to decrease the risk of any diseases. This work presents a computational methodology to automatically diagnose the Improvement of CP children and performance can be evaluated. The alternate medical evaluation techniques have shown their potential for the treatment and diagnosis of disease like strabismus and nystagmus for CP kids. The proposed method is used to measure and quantify the performance improvement by classify the abnormal eye condition of CP kids and these results attained by machine learning method. The results show the best classification accuracy of 94.17% calculated from Neural Network Classifier. Specificity Rate were absorbed as 0.9800 and Sensitivity Rate were absorbed as 0.9165 respectively. The proposed method for non-invasive and automatic detection of abnormalities in CP kids and evaluates the performance improvement more accurately. pubtype: Academic Journal doctype: equations & formulas pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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