Researchers have developed software that detects Alzheimer's using artificial intelligence (AI) at 95% accuracy.
Stevens Institute of Technology researchers have developed software that detects subtle changes in Alzheimer's patients' languages. The AI algorithm could diagnose Alzheimer's even without in-person testing or expensive scans at 95% accuracy. Also, it can explain the diagnosis and allows physicians to re-check the findings.
Late-Onset Alzheimer's - It is the most common type as signs first appear around the mid-60s. It may also be caused by a gene called APOE ɛ4.
Early-Onset Alzheimer's - this is a very rare type of Alzheimer's in which first signs emerge between the 30s and mid-60s. It is also caused by genes that pass down from parent to child.
Aside from genetics, various factors may lead to the development of Alzheimer's. These include the link between vascular conditions and cognitive declines like stroke, high blood pressure, heart disease, as well as metabolic conditions like obesity and diabetes.
Meanwhile, the researchers can also easily incorporate new criteria into the future system, which will make it more accurate. Subbalakshmi explained that the system was designed to be transparent and modular. "If other researchers identify new markers of Alzheimer's, we can simply plug those into our architecture," she added.
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Written by CJ Robles
