Forecasting the prevalence of epilepsy in low- and middle-income countries to 2050 using a hybrid deep neural network-transformer modeling framework: insights from the Global Burden of Disease Study 2023.
- DOI
- 10.1016/j.mmr.2026.100055
- Published
- 2026
- Container
- Military Medical Research
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.1016/j.mmr.2026.100055,
title = {Forecasting the prevalence of epilepsy in low- and middle-income countries to 2050 using a hybrid deep neural network-transformer modeling framework: insights from the Global Burden of Disease Study 2023.},
author = {Zhang ZJ and Wang HF and Cui YS and Lin SN and Jiao H and Meng FG and Feng T},
year = {2026},
journal = {Military Medical Research},
doi = {10.1016/j.mmr.2026.100055},
url = {https://doi.org/10.1016/j.mmr.2026.100055}
}RIS
TY - JOUR TI - Forecasting the prevalence of epilepsy in low- and middle-income countries to 2050 using a hybrid deep neural network-transformer modeling framework: insights from the Global Burden of Disease Study 2023. AU - Zhang ZJ AU - Wang HF AU - Cui YS AU - Lin SN AU - Jiao H AU - Meng FG AU - Feng T PY - 2026 JO - Military Medical Research DO - 10.1016/j.mmr.2026.100055 UR - https://doi.org/10.1016/j.mmr.2026.100055 ER -
APA
ZJ, Z., HF, W., YS, C., SN, L., H, J., FG, M., & T, F. (2026). Forecasting the prevalence of epilepsy in low- and middle-income countries to 2050 using a hybrid deep neural network-transformer modeling framework: insights from the Global Burden of Disease Study 2023.. Military Medical Research. https://doi.org/10.1016/j.mmr.2026.100055
Source records
- pubmed · retrieved 2026-09-26T12:56:09.675Z