Peter D. Galer

Oct 10, 2024 | medrxiv.org | Peter D. Galer |Jillian McKee |Sarah M Ruggiero |Michael Kaufman

The authors have declared no competing interest. EC received support from the NINDS (K23 NS121401-01A1) and the Burroughs Wellcome Fund. IH is supported by the Center for Epilepsy and Neurodevelopmental Disorders (ENDD), NINDS (R01 NS127830-01A1, R01 NS131512-01, and K02 NS112600), St. Jude's (1U24NS120854-02 and 1U24NS120854-03), the Hartwell Foundation (Individual Biomedical Research Award), and the Dravet Foundation. BL is supported by NINDS (DP1NS122038) and The Jonathan Rothberg Family Fund.

Nov 20, 2023 | onlinelibrary.wiley.com | Andrew Knight |Tilo Gschwind |Peter D. Galer |Gregory Worrell

Artificial intelligence (AI) allows data analysis and integration at an unprecedented granularity and scale. Here we review the technological advances, challenges and future perspectives of using AI for electro-clinical phenotyping of animal models and patients with epilepsy. In translational research AI models accurately identify behavioral states in animal models of epilepsy, allowing identification of correlations between neural activity and interictal and ictal behavior.