4 studies on AI’s potential to identify early-stage dementia

A National Institute on Aging-funded research study published in 2020 in the Journal of the American Geriatrics Society evaluated information for more than 16,000 medical check outs of 4,330 patients at Kaiser Permanente Washington health system. The research group established a maker learning design that determined 31 aspects connected with cognitive decrease and was able to flag more than 1,000 gos to that resulted in a patient being diagnosed with dementia. A 2018 research study published in NPJ DIgital Medicine examined the web search behavior of 31,321,773 users.

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Below are four key research studies on the topic.

Medical researchers have increasingly utilized artificial intelligence to examine factors such as patients sleep patterns, speech and typing to determine cases of early-stage dementia faster, according to a Nov. 2 report in The Wall Street Journal.

Katie Adams –
Monday, November 2nd, 2020
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A National Institute on Aging-funded study released in 2020 in the Journal of the American Geriatrics Society examined data for more than 16,000 medical sees of 4,330 patients at Kaiser Permanente Washington health system. The research group developed an artificial intelligence model that determined 31 factors linked with cognitive decrease and was able to flag more than 1,000 check outs that led to a patient being detected with dementia. Almost 500 of those medical diagnoses were for patients whose cognitive modifications were previously undetected.

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In a 2020 study published in Current Alzheimer Research, scientists had nearly 8,900 individuals check out short sentences aloud. Artificial intelligence algorithms were able to accurately figure out which participants were experiencing cognitive problems and which were healthy by evaluating the acoustics of speech.

A 2020 study in EClinicalMedicine taken a look at 270 individuals composed speech patterns for signs of cognitive decrease, accurately distinguished people experiencing cognitive decrease from those who were healthy.

A 2018 research study published in NPJ DIgital Medicine examined the web search behavior of 31,321,773 users. Researchers found that machine knowing algorithms might examine users cursor motions– including speed, tremblings, instructions changes and recurring clicks– to assist spot Parkinsons disease. Early analysis recommends the same method might potentially spot Alzheimers too.