Diagnosis of Alzheimer's disease from neuroimages using steerable quantum probabilistic hamiltonian generative modeling with adaptive chaotic satin bowerbird optimization.
- DOI
- 10.1007/s11571-026-10490-8
- Published
- 2026 Dec
- Container
- Cognitive neurodynamics
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.1007/s11571-026-10490-8,
title = {Diagnosis of Alzheimer's disease from neuroimages using steerable quantum probabilistic hamiltonian generative modeling with adaptive chaotic satin bowerbird optimization.},
author = {Aggarwal K and Ramu V and Padmanaban K and Hemalatha B},
year = {2026},
journal = {Cognitive neurodynamics},
doi = {10.1007/s11571-026-10490-8},
url = {https://doi.org/10.1007/s11571-026-10490-8}
}RIS
TY - JOUR TI - Diagnosis of Alzheimer's disease from neuroimages using steerable quantum probabilistic hamiltonian generative modeling with adaptive chaotic satin bowerbird optimization. AU - Aggarwal K AU - Ramu V AU - Padmanaban K AU - Hemalatha B PY - 2026 JO - Cognitive neurodynamics DO - 10.1007/s11571-026-10490-8 UR - https://doi.org/10.1007/s11571-026-10490-8 ER -
APA
K, A., V, R., K, P., & B, H. (2026). Diagnosis of Alzheimer's disease from neuroimages using steerable quantum probabilistic hamiltonian generative modeling with adaptive chaotic satin bowerbird optimization.. Cognitive neurodynamics. https://doi.org/10.1007/s11571-026-10490-8
Source records
- pubmed · retrieved 2026-09-25T21:43:07.699Z