Multi-Entropy Feature Concatenation for Data-Efficient Cross-Subject Classification of Alzheimer's Disease and Frontotemporal Dementia from Single-Channel EEG.

Li J, Ling C, Zhang W, Lv J, Hu X, Lin K, Yuan J, Zhang S, Chen R

Open source

DOI
10.3390/e28020212
Published
2026 Feb 12
Container
Entropy (Basel, Switzerland)
Publisher
Not recorded
Open access
yes

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BibTeX

@article{allodium:10.3390/e28020212,
  title = {Multi-Entropy Feature Concatenation for Data-Efficient Cross-Subject Classification of Alzheimer's Disease and Frontotemporal Dementia from Single-Channel EEG.},
  author = {Li J and Ling C and Zhang W and Lv J and Hu X and Lin K and Yuan J and Zhang S and Chen R},
  year = {2026},
  journal = {Entropy (Basel, Switzerland)},
  doi = {10.3390/e28020212},
  url = {https://doi.org/10.3390/e28020212}
}

RIS

TY  - JOUR
TI  - Multi-Entropy Feature Concatenation for Data-Efficient Cross-Subject Classification of Alzheimer's Disease and Frontotemporal Dementia from Single-Channel EEG.
AU  - Li J
AU  - Ling C
AU  - Zhang W
AU  - Lv J
AU  - Hu X
AU  - Lin K
AU  - Yuan J
AU  - Zhang S
AU  - Chen R
PY  - 2026
JO  - Entropy (Basel, Switzerland)
DO  - 10.3390/e28020212
UR  - https://doi.org/10.3390/e28020212
ER  - 

APA

J, L., C, L., W, Z., J, L., X, H., K, L., J, Y., S, Z., & R, C. (2026). Multi-Entropy Feature Concatenation for Data-Efficient Cross-Subject Classification of Alzheimer's Disease and Frontotemporal Dementia from Single-Channel EEG.. Entropy (Basel, Switzerland). https://doi.org/10.3390/e28020212

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