A support vectors classifier approach to predicting the risk of progression of adolescent idiopathic scoliosis.

A support vector classifier (SVC) approach was employed in predicting the risk of progression of adolescent idiopathic scoliosis (AIS), a condition that causes visible trunk asymmetries. As the aetiology of AIS is unknown, its risk of progression can only be predicted from measured indicators. Previ...

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Τόπος έκδοσης:	IEEE Transactions on information technology in biomedicine 9, 2 (2005).
Κύριος συγγραφέας:	Ajemba, P.O
Μορφή:	Άρθρο
Γλώσσα:	English
Θέματα:	Lenke indicator. Adolescent idiopathic scoliosis. Aetiology. Brace-treated patient. Clinical indicator. Decision support system. Hypothesis. Logistic regression model. Machine learning. Radiographic indicator. Scoliosis progression risk. Stepwise linear regression model. Support vectors classifier. Visible trunk asymmetry.