reviewMedical Image AnalysisApr 30, 2020HYBRID OA

Convolutional neural networks for classification of Alzheimer's disease: Overview and reproducible evaluation

JWJunhao WenETElina Thibeau–SutreMDMauricio Diaz-MeloJSJorge Samper‐GonzàlezARAlexandre Routier

Centre National de la Recherche Scientifique · Institut national de recherche en sciences et technologies du numérique · +6 more institutions

PubMed
Indexed inarxivcrossrefpubmed

Abstract

Numerous machine learning (ML) approaches have been proposed for automatic classification of Alzheimer's disease (AD) from brain imaging data. In particular, over 30 papers have proposed to use convolutional neural networks (CNN) for AD classification from anatomical MRI. However, the classification performance is difficult to compare across studies due to variations in components such as participant selection, image preprocessing or validation procedure. Moreover, these studies are hardly reproducible because their frameworks are not publicly accessible and because implementation details are lacking. Lastly, some of these papers may report a biased performance due to inadequate or unclear validation or model…

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747
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FWCI
37.49
Percentile
100%
References
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Authors

10

Topics & keywords

Topics
Keywords
  • Overfitting
  • Computer science
  • Artificial intelligence
  • Convolutional neural network
  • Preprocessor
  • Machine learning
  • Pattern recognition (psychology)
  • Support vector machine
UN Sustainable Development Goals
  • Reduced inequalities
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