On the reliability of deep learning-based classification for Alzheimer’s disease: Multi-cohorts, multi-vendors, multi-protocols, and head-to-head validation
- DOI
- 10.3389/fnins.2022.851871
- Published
- 2022-09-07
- Container
- Frontiers in Neuroscience
- Publisher
- Frontiers Media SA
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.3389/fnins.2022.851871,
title = {On the reliability of deep learning-based classification for Alzheimer’s disease: Multi-cohorts, multi-vendors, multi-protocols, and head-to-head validation},
author = {Yeong-Hun Song and Jun-Young Yi and Young Noh and Hyemin Jang and Sang Won Seo and Duk L. Na and Joon-Kyung Seong},
year = {2022},
journal = {Frontiers in Neuroscience},
doi = {10.3389/fnins.2022.851871},
url = {https://doi.org/10.3389/fnins.2022.851871}
}RIS
TY - JOUR TI - On the reliability of deep learning-based classification for Alzheimer’s disease: Multi-cohorts, multi-vendors, multi-protocols, and head-to-head validation AU - Yeong-Hun Song AU - Jun-Young Yi AU - Young Noh AU - Hyemin Jang AU - Sang Won Seo AU - Duk L. Na AU - Joon-Kyung Seong PY - 2022 JO - Frontiers in Neuroscience DO - 10.3389/fnins.2022.851871 UR - https://doi.org/10.3389/fnins.2022.851871 ER -
APA
Song, Y., Yi, J., Noh, Y., Jang, H., Seo, S. W., Na, D. L., & Seong, J. (2022). On the reliability of deep learning-based classification for Alzheimer’s disease: Multi-cohorts, multi-vendors, multi-protocols, and head-to-head validation. Frontiers in Neuroscience. https://doi.org/10.3389/fnins.2022.851871
Source records
- crossref · retrieved 2026-09-27T09:53:15.464Z