hms-harmful-brain-activity-classification
importedsoftware/hms-harmful-brain-activity-classification
Kaggle Silver Medal solution archive for HMS harmful brain activity EEG classification.
Machine-generated from the listed sources and not yet reviewed by a human.
- Category
- Software & Systems
- Subcategory
- unknown
- License
- MIT(osi)
- Status
- active
- Maturity
- deployed
- Organization
- unknown
- Country
- unknown
- Homepage
- unknown
- Documentation
- unknown
- Tags
- deep-learning · eeg · kaggle · medical-ai · pytorch · spectrogram
- Regulatory
- unknown
Computed from shared tags, weighted so a rare tag counts for more than a common one. These are suggestions, not curated relationships.
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Multi-label CV classification with 87% accuracy in detecting correct catheter placement in COVID-19 patient chest x-rays under the Royal Australian and New Zealand College of Radiologists Catheter…
- AttnSleepeeg · pytorch
[TNSRE 2021] "An Attention-based Deep Learning Approach for Sleep Stage Classification with Single-Channel EEG"
- NeuroFloweeg · pytorch
Full-stack real-time EEG analytics and device-ready BCI research platform
- ssvep-multi-task-learningeeg · pytorch
Using multi-task learning to capture signals simultaneously from the fovea efficiently and the neighboring targets in the peripheral vision generate a visual response map. A calibration-free…
Predicting the cost of treatment and insurance using Machine Learning
- api.github.com/repos/YutoTerashima/hms-harmful-brain-activity-classificationretrieved 2026-08-05 · via github-api
Machine-imported from GitHub search. Last push 2026-05-02, 46 stars, license reported as MIT. Category and schematic were assigned by keyword heuristics and are unreviewed.
Not yet verified by a human. Correct this record →
/v1/entries/19.json→ .entries["hms-harmful-brain-activity-classification"]
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