Machine learning-derived Alzheimer's disease dimensions: neuroanatomical, cognitive, clinical, functional, and genetic risk heterogeneity signatures.

Le HN, Ishrat S, Yaghooti B, Murad T, Sapkota R, Thakuri DS, Wong DF, Cruchaga C, for Alzheimer’s Disease Neuroimaging Initiative, Chand GB

Open source

DOI: 10.64898/2026.09.02.26361668
Published: 2026 Sep 7
Container: medRxiv : the preprint server for health sciences
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.64898/2026.09.02.26361668,
  title = {Machine learning-derived Alzheimer's disease dimensions: neuroanatomical, cognitive, clinical, functional, and genetic risk heterogeneity signatures.},
  author = {Le HN and Ishrat S and Yaghooti B and Murad T and Sapkota R and Thakuri DS and Wong DF and Cruchaga C and for Alzheimer’s Disease Neuroimaging Initiative and Chand GB},
  year = {2026},
  journal = {medRxiv : the preprint server for health sciences},
  doi = {10.64898/2026.09.02.26361668},
  url = {https://doi.org/10.64898/2026.09.02.26361668}
}

RIS

TY  - JOUR
TI  - Machine learning-derived Alzheimer's disease dimensions: neuroanatomical, cognitive, clinical, functional, and genetic risk heterogeneity signatures.
AU  - Le HN
AU  - Ishrat S
AU  - Yaghooti B
AU  - Murad T
AU  - Sapkota R
AU  - Thakuri DS
AU  - Wong DF
AU  - Cruchaga C
AU  - for Alzheimer’s Disease Neuroimaging Initiative
AU  - Chand GB
PY  - 2026
JO  - medRxiv : the preprint server for health sciences
DO  - 10.64898/2026.09.02.26361668
UR  - https://doi.org/10.64898/2026.09.02.26361668
ER  -

APA

HN, L., S, I., B, Y., T, M., R, S., DS, T., DF, W., C, C., Initiative, F. A. D. N., & GB, C. (2026). Machine learning-derived Alzheimer's disease dimensions: neuroanatomical, cognitive, clinical, functional, and genetic risk heterogeneity signatures.. medRxiv : the preprint server for health sciences. https://doi.org/10.64898/2026.09.02.26361668

Source records

pubmed · retrieved 2026-11-10T11:20:23.246Z