• The goal of this competition is to detect and classify seizures and other types of harmful brain activity, develop a model trained on electroencephalography (EEG) signals recorded from critically ill hospital patients.
• https://www.acns.org/UserFiles/file/ACNSStandardizedCriticalCareEEGTerminology_rev2021.pdf
• This might help rapidly improve electroencephalography pattern classification accuracy, unlocking transformative benefits for neurocritical care, epilepsy, and drug development. Advancement in this area may allow doctors and brain researchers to detect seizures or other brain damage to provide faster and more accurate treatments.

Citation Jin Jing, Zhen Lin, Chaoqi Yang, Ashley Chow, Sohier Dane, Jimeng Sun, M. Brandon Westover. (2024). HMS - Harmful Brain Activity Classification . Kaggle. https://kaggle.com/competitions/hms-harmful-brain-activity-classification