Automatic classification and prediction models for early Parkinson’s disease diagnosis from SPECT imaging

作者：

Highlights：

• Propose methods for very accurate classification of early PD using only 4 features.

• Used public database which is large and diverse making the developed models robust.

• First study to develop accurate prognostic model based on SBR features for early PD.

摘要

•Propose methods for very accurate classification of early PD using only 4 features.•Used public database which is large and diverse making the developed models robust.•First study to develop accurate prognostic model based on SBR features for early PD.

论文关键词：PD,Parkinson’s disease,PPMI,Parkinson’s progression markers initiative,SPECT,single photon emission computed tomography,SVM,support vector machine,SBR,striatal binding ratio,Computer-aided early diagnosis,Parkinson’s disease,Risk prediction,Pattern analysis,Support vector machine,Logistic regression

论文评审过程：Available online 4 December 2013.

论文官网地址：https://doi.org/10.1016/j.eswa.2013.11.031