Amsterdam Neuroscience

Cross-cohort generalizability of deep and conventional machine learning for MRI-based diagnosis and prediction of Alzheimer's disease

Alzheimer's Disease Neuroimaging Initiative, 1 Jan 2021, In: NeuroImage: Clinical. 31, 102712.

Research output: Contribution to journal › Article › Academic › peer-review

Temporal ordering of multimodal biomarker abnormality in multiple sclerosis

Dekker, I., Schoonheim, M. M., Venkatraghavan, V., Eijlers, A. J. C., Brouwer, I., Wattjes, M. P., Wink, A. M., Geurts, J. J. G., Uitdehaag, B. M. J., Oxtoby, N. P., Vrenken, H., Killestein, J., Barkhof, F. & Wottschel, V., Sept 2019, In: MULTIPLE SCLEROSIS JOURNAL. 25, p. 461-462

Research output: Contribution to journal › Meeting Abstract › Academic

Predicting Cognitive Decline in Amyloid-Positive Patients With Mild Cognitive Impairment or Mild Dementia

Alzheimer's Disease Neuroimaging Initiative (ADNI), 10 Jul 2024, In: Neurology. 103, 3, p. e209605 e209605.

Research output: Contribution to journal › Article › Academic › peer-review

Amyloid pathology and vascular risk are associated with distinct patterns of cerebral white matter hyperintensities: A multicenter study in 3132 memory clinic patients

Biesbroek, J. M., Coenen, M., DeCarli, C., Fletcher, E. M., Maillard, P. M., Barkhof, F., Barnes, J., Benke, T., Chen, C. P. L. H., Dal-Bianco, P., Dewenter, A., Duering, M., Enzinger, C., Ewers, M., Exalto, L. G., Franzmeier, N., Hilal, S., Hofer, E., Koek, H. L., Maier, A. B., & 20 othersMcCreary, C. R., Papma, J. M., Paterson, R. W., Pijnenburg, Y. A. L., Rubinski, A., Schmidt, R., Schott, J. M., Slattery, C. F., Smith, E. E., Sudre, C. H., Steketee, R. M. E., Teunissen, C. E., van den Berg, E., van der Flier, W. M., Venketasubramanian, N., Venkatraghavan, V., Vernooij, M. W., Wolters, F. J., Xin, X. & Alzheimer's Disease Neuroimaging Initiative, 1 Apr 2024, In: Alzheimer's and Dementia. 20, 4, p. 2980-2989 10 p.

Research output: Contribution to journal › Article › Academic › peer-review

Cerebrospinal fluid proteomics in patients with Alzheimer’s disease reveals five molecular subtypes with distinct genetic risk profiles

Tijms, B. M., Vromen, E. M., Mjaavatten, O., Holstege, H., Reus, L. M., van der Lee, S., Wesenhagen, K. E. J., Lorenzini, L., Vermunt, L., Venkatraghavan, V., Tesi, N., Tomassen, J., den Braber, A., Goossens, J., Vanmechelen, E., Barkhof, F., Pijnenburg, Y. A. L., van der Flier, W. M., Teunissen, C. E., Berven, F. S., & 1 othersVisser, P. J., Jan 2024, In: Nature Aging. 4, 1, p. 33-47 15 p.

Research output: Contribution to journal › Article › Academic › peer-review