Machine learning prediction for epilepsy treatment selection and prognosis: achievements and challenges.
- DOI
- 10.1016/j.landig.2026.101022
- Published
- 2026 Sep
- Container
- The Lancet. Digital health
- Publisher
- Not recorded
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1016/j.landig.2026.101022,
title = {Machine learning prediction for epilepsy treatment selection and prognosis: achievements and challenges.},
author = {Chen Z and Li X and Jehi L and Ge Z and Wang X and Kwan P},
year = {2026},
journal = {The Lancet. Digital health},
doi = {10.1016/j.landig.2026.101022},
url = {https://doi.org/10.1016/j.landig.2026.101022}
}RIS
TY - JOUR TI - Machine learning prediction for epilepsy treatment selection and prognosis: achievements and challenges. AU - Chen Z AU - Li X AU - Jehi L AU - Ge Z AU - Wang X AU - Kwan P PY - 2026 JO - The Lancet. Digital health DO - 10.1016/j.landig.2026.101022 UR - https://doi.org/10.1016/j.landig.2026.101022 ER -
APA
Z, C., X, L., L, J., Z, G., X, W., & P, K. (2026). Machine learning prediction for epilepsy treatment selection and prognosis: achievements and challenges.. The Lancet. Digital health. https://doi.org/10.1016/j.landig.2026.101022
Source records
- pubmed · retrieved 2026-09-26T00:17:01.644Z