Dasion provides accurate, fast and explainable EEG Machine Learning Technologies to EEG companies, hospitals and doctors by identifying patterns and biomarkers in EEG data to distinguish Brain tumors, mTBI, Alzeihmer’s, Parkinson’s diseases, and sleep disorders.
Dasion's Geometric Unified Learning (GUL) tools have capabilities of vectorizing EEG data features, compressing EEG data, searching and learning simultaneously, with highly interpretable results. When the technology makes predictions of the above diseases, it gives patterns for each different disease. It will show the user exactly which data points are responsible for those predictions.
Mild Traumatic Brain Injury (mTBI) is a common brain injury and affects a diverse group of people: soldiers, constructors, athletes, drivers, children, elders, and nearly everyone. Thus, having a well established, fast, cheap, and accurate classification method is crucial for the well-being of people around the globe. Luckily, using Machine Learning (ML) on electroencephalography (EEG) data shows promising results. Dasion has analyzed the most cutting-edge technologies. We reviewed, summarized, and compared the fourteen most cutting-edge machine learning research papers for predicting and classifying mTBI in terms of 1) EEG data types, 2) data preprocessing methods, 3) machine learning feature representations, 4) feature extraction methods, and 5) machine learning classifiers and predictions.
In fact, Dasion is also developing similar technologies for detecting other neurological disorders, creating AI technology for taking care of stroke patients, and understanding brain functions by creating cutting-edge AI technology to help companies like you.