About 6 million people in the US are currently living with Alzheimer's disease, the most common form of dementia, according to the Alzheimer's Association. Despite being the sixth-leading cause of death in the country, there is currently no known cure for the memory-robbing condition. But diagnosing the disease early can help people seek preventative care and slow its progress. That's why a team of students at USC is developing machine learning tools to detect early-onset Alzheimer's disease using speech patterns, and democratize the diagnosis process. The team started working on the system in spring 2021 as a project for CAIS, the student branch of the Center for Artificial Intelligence in Society, in collaboration with students from MEDesign, the biomedical engineering design group.