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Machine learning techniques distinguish very mild dementia from normal cognition using MRI

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Machine-learning techniques for building a diagnostic model for very mild dementia Rong Chen & Edward H. Herskovits University of Pennsylvania NeuroImage, 2010 Journal Club - Omid Cinco de Mayo, 2010
Overview ,[object Object],[object Object],[object Object],[object Object],[object Object]
Clinical Question ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],* Alzheimer’s Disease Research Center
Approach: Machine Learning Classification ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Training Data / Patterns Y 1 Y 2 . . . Y N Known Labels Testing Data / Patterns Predicted Labels
Approach: Classification ,[object Object],LDA LR
Approach: Classification ,[object Object],[object Object]
Methods
Image Processing ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],RAVENS = Regional Analysis of Volumes Embedded in Stereotaxic Space
Naïve Bayes (NB) ,[object Object],[object Object],[object Object]
Decision Trees ,[object Object],[object Object],[object Object],[object Object],[object Object],Node/Structure Node/Structure rule rule A B A
Support Vector Machines (SVM) ,[object Object],[object Object]
Multiple Layer Perceptrons (MLP) ,[object Object],[object Object],[object Object],[object Object],R C
Performance Comparison ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Performance Comparison ,[object Object],[object Object],[object Object],[object Object]
Results
[object Object],[object Object],[object Object]
Performance of all 7 algorithms on 91 atlas structures RH - right hippocampus LPG - left parahippocampal gyrus RSN - right subthalamic nucleus RNA - right nucleus accumbens LC - left cuneus LPG - left precentral gyrus RC - right cuneus LITG - left inferior temporal gyrus RAG - right angular gyrus Some algorithms (BNCIT, Decision trees, discriminant analysis and logistic regression) select subset of features for classification; others use all features (91 atlas structures)
BNCIT ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Decision Trees RH - right hippocampus LPG - left parahippocampal gyrus RSN - right subthalamic nucleus RNA - right nucleus accumbens LC - left cuneus LPG - left precentral gyrus RC - right cuneus LITG - left inferior temporal gyrus RAG - right angular gyrus
Performance of all 7 algorithms on 12 atlas structures (near or in medial temporal lobe) BNCIT: same model as before (only RH is included)
New decision tree:
Receiver Operating Characteristic (ROC) curves: areas under the curve (AUC) of all 7 algorithms for both experiments mismatch between AUCs and accuracies (reported before)
Comparison of algorithms through triangular discriminant metrics ,[object Object]
Algorithm “Families” “Rule”-based: NB, BNCIT, DT “Margin”-based: SVM, MLP “Statistics”-based: LDA, LR
Conclusions ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
A few strengths ,[object Object],[object Object]
Thank you!

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Machine learning techniques distinguish very mild dementia from normal cognition using MRI

  • 1. Machine-learning techniques for building a diagnostic model for very mild dementia Rong Chen & Edward H. Herskovits University of Pennsylvania NeuroImage, 2010 Journal Club - Omid Cinco de Mayo, 2010
  • 2.
  • 3.
  • 4.
  • 5.
  • 6.
  • 8.
  • 9.
  • 10.
  • 11.
  • 12.
  • 13.
  • 14.
  • 16.
  • 17. Performance of all 7 algorithms on 91 atlas structures RH - right hippocampus LPG - left parahippocampal gyrus RSN - right subthalamic nucleus RNA - right nucleus accumbens LC - left cuneus LPG - left precentral gyrus RC - right cuneus LITG - left inferior temporal gyrus RAG - right angular gyrus Some algorithms (BNCIT, Decision trees, discriminant analysis and logistic regression) select subset of features for classification; others use all features (91 atlas structures)
  • 18.
  • 19. Decision Trees RH - right hippocampus LPG - left parahippocampal gyrus RSN - right subthalamic nucleus RNA - right nucleus accumbens LC - left cuneus LPG - left precentral gyrus RC - right cuneus LITG - left inferior temporal gyrus RAG - right angular gyrus
  • 20. Performance of all 7 algorithms on 12 atlas structures (near or in medial temporal lobe) BNCIT: same model as before (only RH is included)
  • 22. Receiver Operating Characteristic (ROC) curves: areas under the curve (AUC) of all 7 algorithms for both experiments mismatch between AUCs and accuracies (reported before)
  • 23.
  • 24. Algorithm “Families” “Rule”-based: NB, BNCIT, DT “Margin”-based: SVM, MLP “Statistics”-based: LDA, LR
  • 25.
  • 26.