AI and Alzheimer’s
by Diya Sivasubramani
STEM is such a vast field, and more often than not, a combination of various aspects of STEM allows for innovative research. From enhancing our problem-solving skills to landing the first men on the moon, interdisciplinary aspects of STEM have touched our lives. Recently, a combination of artificial intelligence and the neurological sciences have led researchers to find possible ways to diagnose, monitor, and treat Alzheimer’s.
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Alzheimer’s: an incurable, progressive disease that typically occurs in the older population. As the most common form of dementia, it causes the decline of cells in the brain that relate to memory, instigating a deterioration of cognitive ability. With the knowledge that amyloid plaques and tau tangles are signifiers that there is a chance that an individual has Alzheimer’s, people can be checked for Alzheimer’s through a test using cerebrospinal fluids. Unfortunately, these tests are usually time-consuming and require a large sample. However, a group of researchers from Swansea University was able to use machine learning and the properties of non-Newtonian fluids to analyze and create tests that determine the possibility of Alzheimer’s with a quick turnaround time and a minuscule amount of biofluid.
Winterlight, an AI-related company, analyzed the trials of Genentech, a biotech company, and developed a test that monitors the progression of Alzheimer’s through speech analysis. Through their observations, Winterlight was able to identify over five hundred different vocal markers that encapsulated various attributes of linguistics. They used these markers to build an AI algorithm that allowed for a more accurate diagnosis for doctors monitoring Alzheimer’s patients.
Additionally, Xilin Liu, a researcher that works with the University of Toronto and the University Health Network, is researching the use of neurological implants as a way to treat Alzheimer’s as well as the use of AI to maximize the efficiency and safety of this method. In theory, neurons in the brain can be turned on and off, and these neural implants should be able to copy the neuron’s niches. To adjust the neural implants to their specific user, a form of AI is used: deep learning. This technology allows deep-level information to be extracted once the original algorithm is trained. Although the research involving neural engineering is still emerging, this research has proven to be groundbreaking and is paving a possible path to treatments for Alzheimer’s patients.
Research involving Alzheimer’s has come a long way thanks to the interdisciplinary aspects of STEM; the connection between AI and medicine provides for more efficient and valuable solutions to finding ways to treat neurological disorders.
Bibliography:
https://medicalxpress.com/news/2022-10-combines-ai-microelectronics-neural-implants.html
