HMS - Harmful Brain Activity Classification

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

Name		Name	Last commit message	Last commit date
Latest commit History 29 Commits
example_figures		example_figures
saved_models		saved_models
.gitignore		.gitignore
Dev_1.5.ipynb		Dev_1.5.ipynb
Dev_1.ipynb		Dev_1.ipynb
Dev_2.ipynb		Dev_2.ipynb
Initial_model.py		Initial_model.py
README.md		README.md
dev3_IC.ipynb		dev3_IC.ipynb
hms-hbac-kerascv-starter-notebook.ipynb		hms-hbac-kerascv-starter-notebook.ipynb
resnet_224.ipynb		resnet_224.ipynb
rew.ipynb		rew.ipynb
sample_submission.csv		sample_submission.csv
submission.csv		submission.csv
test.csv		test.csv
train.csv		train.csv

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