The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Estimating the age of healthy subjects from T1-weighted MRI scans using kernel methods: Exploring the influence of various parameters
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Citations
Cites
Gene selection for cancer classification using support vector machines
Guyon, I., Weston, J., Barnhill, S., & Vapnik, V. (2002) · Machine Learning · doi:10.1023/a:1012487302797 · Cited by 9,954
The Clinical Dementia Rating (CDR): Current version and scoring rules
Morris, J. C. (1993) · Neurology · doi:10.1212/wnl.43.11.2412-a · Cited by 9,882
A fast diffeomorphic image registration algorithm
Ashburner, J. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2007.07.007 · Cited by 8,122
A Voxel-Based Morphometric Study of Ageing in 465 Normal Adult Human Brains
Good, C. D., Johnsrude, I. S., Ashburner, J., Henson, R. N. A., Friston, K. J., & Frackowiak, R. S. J. (2001) · NeuroImage · doi:10.1006/nimg.2001.0786 · Cited by 4,561
Longitudinal Magnetic Resonance Imaging Studies of Older Adults: A Shrinking Brain
Resnick, S. M., Pham, D. L., Kraut, M. A., Zonderman, A. B., & Davatzikos, C. (2003) · The Journal of Neuroscience · doi:10.1523/jneurosci.23-08-03295.2003 · Cited by 1,425
Cited by
Orrù, G., Pettersson-Yeo, W., Marquand, A. F., Sartori, G., & Mechelli, A. (2012) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2012.01.004 · Cited by 1,012
Single subject prediction of brain disorders in neuroimaging: Promises and pitfalls
Arbabshirani, M. R., Plis, S., Sui, J., & Calhoun, V. D. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2016.02.079 · Cited by 912
Cole, J. H., Poudel, R. P. K., Tsagkrasoulis, D., Caan, M. W. A., Steves, C., Spector, T. D., & Montana, G. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.07.059 · Cited by 872
“Data pre-processing is almost ubiquitous in neuroimaging, including in previous studies using brain-based age predictions (Cole et al., 2015; Franke et al., 2010; Irimia et al., 2014; Schnack et al., 2016; Steffener et al., 2016).”
BackgroundMethodResultInfluentialCole, J. H., Ritchie, S. J., Bastin, M. E., Valdés Hernández, M. C., Muñoz Maniega, S., Royle, N., Corley, J., Pattie, A., Harris, S. E., Zhang, Q., et al. (2018) · Molecular Psychiatry · doi:10.1038/mp.2017.62 · Cited by 831
Understanding heterogeneity in clinical cohorts using normative models: Beyond case-control studies
Marquand, A. F., Rezek, I., Buitelaar, J., & Beckmann, C. F. (2016) · Biological Psychiatry · doi:10.1016/j.biopsych.2015.12.023 · Cited by 683
Metadata
- Authors
- Franke, K., Ziegler, G., Klöppel, S., & Gaser, C.
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2010-04
- Volume
- 50
- Issue
- 3
- Pages
- 883-892
- ISSN
- 1053-8119 (ISSN-L)
- OpenAlex
- W2113127248
- Cited by
- 794
- References
- 5
- FWCI
- 9.57
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Estimating the age of healthy subjects from T1-weighted MRI scans using kernel methods: Exploring the influence of various parameters. https://app.cochat.ai/papers/10.1016/j.neuroimage.2010.01.005
- The paper
- Franke, K., Ziegler, G., Klöppel, S., & Gaser, C. (2010). Estimating the age of healthy subjects from T1-weighted MRI scans using kernel methods: Exploring the influence of various parameters. NeuroImage. https://doi.org/10.1016/j.neuroimage.2010.01.005
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
