Adaptive 3DCNN-based Interpretable Ensemble Model for Early Diagnosis of Alzheimer's Disease.
- DOI
- 10.1109/tcss.2022.3223999
- Published
- 2022-11-30
- Container
- IEEE Trans Comput Soc Syst
- Publisher
- Not recorded
- Open access
- no
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Cite this work
BibTeX
@article{allodium:10.1109/tcss.2022.3223999,
title = {Adaptive 3DCNN-based Interpretable Ensemble Model for Early Diagnosis of Alzheimer's Disease.},
author = {Pan D and Luo G and Zeng A and Zou C and Liang H and Wang J and Zhang T and Yang B and Alzheimer’s Disease Neuroimaging Initiative (ADNI).},
year = {2024},
journal = {IEEE Trans Comput Soc Syst},
doi = {10.1109/tcss.2022.3223999},
url = {https://doi.org/10.1109/tcss.2022.3223999}
}RIS
TY - JOUR TI - Adaptive 3DCNN-based Interpretable Ensemble Model for Early Diagnosis of Alzheimer's Disease. AU - Pan D AU - Luo G AU - Zeng A AU - Zou C AU - Liang H AU - Wang J AU - Zhang T AU - Yang B AU - Alzheimer’s Disease Neuroimaging Initiative (ADNI). PY - 2024 JO - IEEE Trans Comput Soc Syst DO - 10.1109/tcss.2022.3223999 UR - https://doi.org/10.1109/tcss.2022.3223999 ER -
APA
D, P., G, L., A, Z., C, Z., H, L., J, W., T, Z., B, Y., & (ADNI)., A. D. N. I. (2024). Adaptive 3DCNN-based Interpretable Ensemble Model for Early Diagnosis of Alzheimer's Disease.. IEEE Trans Comput Soc Syst. https://doi.org/10.1109/tcss.2022.3223999
Source records
- europe-pmc · retrieved 2026-11-10T13:54:45.531Z