Brain Advance Access published online on May 21, 2008
Brain, doi:10.1093/brain/awn091
© The Author (2008).
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
A plea for confidence intervals and consideration of generalizability in diagnostic studies
1Department of Psychiatry, University Clinic Freiburg, Freiburg, Germany, 2Wellcome Trust Centre for Neuroimaging, Institute of Neurology, University College London, London, United Kingdom, 3Department of Psychiatry and Psychology, Mayo Clinic, Scottsdale, AZ, USA (CMS) and Department of Radiology, Mayo Clinic, Rochester, MN, USA (CRJ), 4Dementia Research Centre, Department of Neurodegenerative Disease, Institute of Neurology, University College London, London, United Kingdom, 5Département d'études cognitives, Ecole Normale Supérieure, Paris, France and 6Laboratory of Neuroimaging, IRCCS Santa Lucia, Roma, Italy
Correspondence to:
Stefan Klöppel, MD, Department of Psychiatry, Hauptstr. 5, 79104 Freiburg, Germany E-mail: stefan.kloeppel@uniklinik-freiburg.de
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Received April 18, 2008. Accepted April 18, 2008.
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Sir, Many thanks for letting us respond to the interesting letter concerning our recent paper. We are grateful for the chance to clarify the points raised, which suggest our conclusions were too optimistic. In our paper (Kloppel et al., 2008
), we used MRI scans from pathologically proven cases of Alzheimer's disease and frontotemporal lobar degeneration (FTLD) to validate trained sets for a machine learning-based support vector machine (SVM) approach to the categorization of structural scans