Seizure-Semiology-Suite (S3): A Clinically Multimodal Dataset, Benchmark, and Models for Seizure Semiology Understanding
arXiv cs.CV·Lina Zhang, Tonmoy Monsoor, Peizheng Li, Jiarui Cui, Xinyi Peng, Chong Han, Prateik Sinha, Siyuan Dai, Jessica Nichole Pasqua, Colin M McCrimmon, Weiting Liu, Hailey Marie Miranda, Bing Hu, Xiangting Wu, Tengyou Xu, Chunhan Li, Jiaye Tian, Jiarui Tang, Detao Ma, Lingye Kong, Junnan Lyu, Jungang Li, Yan Zan, Junhua Huang, Rajarshi Mazumder, Vwani Roychowdhury
15h agoQuick Take
Seizure-Semiology-Suite introduces a dataset and benchmark for understanding seizure semiology using MLLMs.
Key Points
- 438 seizure videos with 35,000+ annotations.
- Seven-task benchmark evaluates MLLMs' performance.
- Fine-tuning improves classification accuracy significantly.
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