Machine learning–integrated cortical feature analysis identifies cortical complexity as a discriminative feature in autism spectrum disorder
- DOI
- 10.1016/j.pscychresns.2026.112372
- Published
- 2027-03
- Container
- Psychiatry Research: Neuroimaging
- Publisher
- Elsevier BV
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1016/j.pscychresns.2026.112372,
title = {Machine learning–integrated cortical feature analysis identifies cortical complexity as a discriminative feature in autism spectrum disorder},
author = {Minghao Xu and Hassan Shayan and Han-Gue Jo},
year = {2027},
journal = {Psychiatry Research: Neuroimaging},
doi = {10.1016/j.pscychresns.2026.112372},
url = {https://doi.org/10.1016/j.pscychresns.2026.112372}
}RIS
TY - JOUR TI - Machine learning–integrated cortical feature analysis identifies cortical complexity as a discriminative feature in autism spectrum disorder AU - Minghao Xu AU - Hassan Shayan AU - Han-Gue Jo PY - 2027 JO - Psychiatry Research: Neuroimaging DO - 10.1016/j.pscychresns.2026.112372 UR - https://doi.org/10.1016/j.pscychresns.2026.112372 ER -
APA
Xu, M., Shayan, H., & Jo, H. (2027). Machine learning–integrated cortical feature analysis identifies cortical complexity as a discriminative feature in autism spectrum disorder. Psychiatry Research: Neuroimaging. https://doi.org/10.1016/j.pscychresns.2026.112372
Source records
- crossref · retrieved 2026-11-10T09:08:34.297Z