Explainable Machine Learning for Predicting Early Response to Perampanel in Pediatric Epilepsy: A Real-World Study

Xin Rao, Ping Wu, Xi Lin, Jie-Min Zhang, Xiao-Jun Lin, Zhou-Jie Liu, Rong-Fang Lin, Yue-Wen Chen

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DOI: 10.2147/dddt.s648788
Published: 2026-10
Container: Drug Design, Development and Therapy
Publisher: Informa UK Limited
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.2147/dddt.s648788,
  title = {Explainable Machine Learning for Predicting Early Response to Perampanel in Pediatric Epilepsy: A Real-World Study},
  author = {Xin Rao and Ping Wu and Xi Lin and Jie-Min Zhang and Xiao-Jun Lin and Zhou-Jie Liu and Rong-Fang Lin and Yue-Wen Chen},
  year = {2026},
  journal = {Drug Design, Development and Therapy},
  doi = {10.2147/dddt.s648788},
  url = {https://doi.org/10.2147/dddt.s648788}
}

RIS

TY  - JOUR
TI  - Explainable Machine Learning for Predicting Early Response to Perampanel in Pediatric Epilepsy: A Real-World Study
AU  - Xin Rao
AU  - Ping Wu
AU  - Xi Lin
AU  - Jie-Min Zhang
AU  - Xiao-Jun Lin
AU  - Zhou-Jie Liu
AU  - Rong-Fang Lin
AU  - Yue-Wen Chen
PY  - 2026
JO  - Drug Design, Development and Therapy
DO  - 10.2147/dddt.s648788
UR  - https://doi.org/10.2147/dddt.s648788
ER  -

APA

Rao, X., Wu, P., Lin, X., Zhang, J., Lin, X., Liu, Z., Lin, R., & Chen, Y. (2026). Explainable Machine Learning for Predicting Early Response to Perampanel in Pediatric Epilepsy: A Real-World Study. Drug Design, Development and Therapy. https://doi.org/10.2147/dddt.s648788

Source records

crossref · retrieved 2026-11-10T11:33:08.954Z