2025 Grant Recipients – Emre Sezgin, Anup Patel, & Zach Grinspan

Artificial Intelligence for LGS and Epilepsy Registry Creation to Improve the Health Outcomes

Highlights:

• Leverage advanced AI techniques to extract LGS-specific clinical data from electronic health records and create a scalable, AI-assisted registry.
• Aim to capture key LGS-related variables such as seizure dynamics, treatment responses, and EEG biomarkers.
• A valuable resource for future LGS research. 

Results: Grant in Progress

Results will be shared when the grant is completed.

Lay Abstract:

Current treatments for LGS are often ineffective, and managing this complex condition is challenging due to the variability in symptoms and underlying causes. Additionally, there is no comprehensive system that tracks LGS patients over time, which makes it hard for researchers and doctors to develop better treatment strategies or discover new therapies.

To address this gap, we propose creating a comprehensive LGS patient registry, which will collect and analyze data from health records over time. We will use artificial intelligence (AI) tools, like natural language processing (NLP) and large language models (LLMs), to automatically gather information from medical records. This innovative approach will reduce the costs and labor associated with traditional registry creation, allowing for a more detailed and accurate understanding of LGS. By building this registry, we aim to improve the care of LGS patients and open the door to future research on better treatments and potential prevention strategies. The long-term goal is to extend this AI-assisted approach to other rare and complex neurological disorders.

Updated 02/09/26 (KK)