HMS - Harmful Brain Activity Classification Overview Welcome to the HMS - Harmful Brain Activity Classification competition! The goal of this competition is to detect and classify seizures and other types of harmful brain activity in critically ill hospital patients. You'll be working with electroencephalography (EEG) signals recorded from these patients.

Data The dataset contains EEG signals recorded from critically ill patients, along with labels indicating different types of harmful brain activity, including seizures. Your task is to develop a model that accurately classifies these EEG signals.

Code You can use your preferred programming language and machine learning libraries to analyze the EEG data and build your classification model. We encourage you to explore various signal processing techniques, feature extraction methods, and deep learning architectures to achieve the best classification performance.

Models Experiment with different machine learning and deep learning models to classify EEG signals effectively. Consider techniques such as convolutional neural networks (CNNs), recurrent neural networks (RNNs), and attention mechanisms to capture temporal dependencies in the EEG data.

Discussion Join the discussion forum to collaborate with other participants, share insights, and exchange ideas. Collaboration can lead to innovative approaches and better solutions to the classification task.

Leaderboard Track your progress on the leaderboard and see how your model ranks against other participants. Continuous evaluation and improvement are essential for achieving high performance in this competition.

Rules Please review the competition rules and guidelines to ensure fair participation and adherence to the competition regulations. Respect the privacy and confidentiality of the patients whose data is included in the dataset.

Team You can compete individually or form teams with other participants to work on the classification task collaboratively. Teamwork can lead to synergistic solutions and foster a supportive learning environment.

Submissions Submit your predictions before the deadline to be considered for the final evaluation. Your contributions may have a significant impact on neurocritical care, epilepsy treatment, and drug development.

Let's work together to advance harmful brain activity classification and improve patient outcomes in critical care settings