The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.
Combining MRI and CSF measures for classification of Alzheimer's disease and prediction of mild cognitive impairment conversion
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McKhann, G. M., Knopman, D. S., Chertkow, H., Hyman, B. T., Jack, C. R., Kawas, C. H., Klunk, W. E., Koroshetz, W. J., Manly, J. J., Mayeux, R., et al. (2011) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2011.03.005 · Cited by 18,657
Desikan, R. S., Ségonne, F., Fischl, B., Quinn, B. T., Dickerson, B. C., Blacker, D., Buckner, R. L., Dale, A. M., Maguire, R. P., Hyman, B. T., et al. (2006) · NeuroImage · doi:10.1016/j.neuroimage.2006.01.021 · Cited by 13,324
PLS-regression: a basic tool of chemometrics
Wold, S., Sjöström, M., & Eriksson, L. (2001) · Chemometrics and Intelligent Laboratory Systems · doi:10.1016/s0169-7439(01)00155-1 · Cited by 10,084
Fischl, B., Salat, D. H., Busa, E., Albert, M., Dieterich, M., Haselgrove, C., van der Kouwe, A., Killiany, R., Kennedy, D., Klaveness, S., et al. (2002) · Neuron · doi:10.1016/s0896-6273(02)00569-x · Cited by 8,610
A nonparametric method for automatic correction of intensity nonuniformity in MRI data
Sled, J. G., Zijdenbos, A. P., & Evans, A. C. (1998) · IEEE Transactions on Medical Imaging · doi:10.1109/42.668698 · Cited by 4,731
Wold, S., Ruhe, A., Wold, H., & Dunn, III (1984) · SIAM Journal on Scientific and Statistical Computing · doi:10.1137/0905052 · Cited by 2,529
Comparing predictors of conversion and decline in mild cognitive impairment
Landau, S. M., Harvey, D., Madison, C. M., Reiman, E. M., Foster, N. L., Aisen, P. S., Petersen, R. C., Shaw, L. M., Trojanowski, J. Q., Jack, C. R., et al. (2010) · Neurology · doi:10.1212/wnl.0b013e3181e8e8b8 · Cited by 616
Consistent neuroanatomical age-related volume differences across multiple samples
Walhovd, K. B., Westlye, L. T., Amlien, I., Espeseth, T., Reinvang, I., Raz, N., Agartz, I., Salat, D. H., Greve, D. N., Fischl, B., et al. (2011) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2009.05.013 · Cited by 506
Boosting power for clinical trials using classifiers based on multiple biomarkers
Kohannim, O., Hua, X., Hibar, D. P., Lee, S., Chou, Y.-Y., Toga, A. W., Jack, C. R., Weiner, M. W., & Thompson, P. M. (2010) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2010.04.022 · Cited by 190 · cited 9×
“Kohannim et al. (2010) have also combined MRI, CSF and FDG-PET in a smaller cohort.”
BackgroundResultInfluential
Cited by
Hierarchical Feature Representation and Multimodal Fusion with Deep Learning for AD/MCI Diagnosis
Suk, H.-I., Lee, S.-W., & Shen, D. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2014.06.077 · Cited by 968
“…it is noteworthy that unlike the previous approaches (Hinrichs et al., 2011; Kohannim et al., 2010; Liu et al., 2012, 2013; Walhovd et al., 2010; Westman et al., 2012; Zhang and Shen, 2012; Zhang et al., 2011) that considered simple low-level features, which are often vulnerable to noises, we…”
InfluentialA Deep Learning Model to Predict a Diagnosis of Alzheimer Disease by Using 18 F-FDG PET of the Brain
Ding, Y., Sohn, J. H., Kawczynski, M. G., Trivedi, H., Harnish, R., Jenkins, N. W., Lituiev, D., Copeland, T. P., Aboian, M. S., Mari Aparici, C., et al. (2019) · Radiology · doi:10.1148/radiol.2018180958 · Cited by 577
BrainAGE in Mild Cognitive Impaired Patients: Predicting the Conversion to Alzheimer’s Disease
Gaser, C., Franke, K., Klöppel, S., Koutsouleris, N., Sauer, H., & Initiative, A. D. N. (2013) · PLoS ONE · doi:10.1371/journal.pone.0067346 · Cited by 538
Islam, J., & Zhang, Y. (2018) · Brain Informatics · doi:10.1186/s40708-018-0080-3 · Cited by 478
Weiner, M. W., Veitch, D. P., Aisen, P. S., Beckett, L. A., Cairns, N. J., Cedarbaum, J., Green, R. C., Harvey, D., Jack, C. R., Jagust, W., et al. (2015) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2014.11.001 · Cited by 348
Metadata
- Authors
- Westman, E., Muehlboeck, J.-S., & Simmons, A.
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2012-08
- Volume
- 62
- Issue
- 1
- Pages
- 229-238
- ISSN
- 1053-8119 (ISSN-L)
- OpenAlex
- W2078551663
- Cited by
- 302
- References
- 9
- FWCI
- 18.86
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Combining MRI and CSF measures for classification of Alzheimer's disease and prediction of mild cognitive impairment conversion. https://app.cochat.ai/papers/10.1016/j.neuroimage.2012.04.056
- The paper
- Westman, E., Muehlboeck, J.-S., & Simmons, A. (2012). Combining MRI and CSF measures for classification of Alzheimer's disease and prediction of mild cognitive impairment conversion. NeuroImage. https://doi.org/10.1016/j.neuroimage.2012.04.056
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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.
