Over 44 million people worldwide live with Alzheimer’s disease, and due to the costs and complications related to diagnosis, around 33 million people do not have access to treatment options, care, or support. This is because Alzheimer's diagnosis today is primarily conducted by PET, CT, and MRI screening. These procedures are lengthy, expensive, and complicated, explaining why it may take up to 2 years for patients to get the care that they need.
Alzheimer's is the most expensive disease in America, costing more than cancer and heart disease. Caring for those with Alzheimer's and other dementias will total an estimated $236 billion. In some cases, diagnosing Alzheimer’s may take up to years, and thus being able to utilize diagnostic tools that warns patients of the gruesome disease in advance increases the quality of healthcare dramatically. Alzheimer’s impacts an enormous number of people, and being able to diagnose it and mark common traits between patients is a meaningful step in the improvement of healthcare.
Our team has meta-compiled research from around the world that indicates a clear relationship between distinct EEG biomarkers and early onset of Alzheimer's and is expecting to apply machine learning algorithms to these data sets in order to output a probability of a patient contracting the disease.
The funds we raise will be put towards buying parts to build and manufacture a more accurate version (yet equivalently portable EEG machine). In addition we will be using the money to file for patents, buying additional electrodes for an active comprehensive electrode map, as well as purchasing waveform analytic software. We will pay for data as needed, as study data for machine learning and classification training sets is not easy to acquire, and is often kept private by companies and institutions. In the further future the funds could be used to mass manufacture the goods instead of making them individually.
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