A multimodal clinical data resource for personalized risk assessment of sudden unexpected death in epilepsy

• Published in: Frontiers in big data Vol. 5; p. 965715
• Main Authors: Li, Xiaojin, Tao, Shiqiang, Lhatoo, Samden D., Cui, Licong, Huang, Yan, Hampson, Johnson P., Zhang, Guo-Qiang
• Format: Journal Article
• Language: English
• Published: Switzerland Frontiers Media S.A 17.08.2022
• Subjects: Big Data; epilepsy; machine learning; multimodal clinical data resource; ontology-driven system design; personalized risk assessment; sudden unexpected death in epilepsy (SUDEP); epilepsy; personalized risk assessment; deep learning; sudden unexpected death in epilepsy (SUDEP); ontology-driven system design; multimodal clinical data resource; machine learning

Epilepsy affects ~2–3 million individuals in the United States, a third of whom have uncontrolled seizures. Sudden unexpected death in epilepsy (SUDEP) is a catastrophic and fatal complication of poorly controlled epilepsy and is the primary cause of mortality in such patients. Despite its huge publ...