Alzheimer’s disease, a neurodegenerative condition, deadly in its effects, is notoriously hard for doctors to diagnose. They have only one certain way to diagnose it: by examining a patient’s brain once he/she has passed away during an autopsy. As far as Alzheimer detection goes, detecting the early stages of the disease is very difficult. However, according to research, AI can recognize the changes in a person’s makeup that an Alzheimer’s patient goes through. AI can recognize them early, identifying those who are at risk of developing the disease.
AI and Alzheimer Detection
Different teams of scientists have created AI algorithms, one team at McGill University, Canada, the other at the University of Bari, Italy. These algorithms examine the brains of people who exhibit memory loss, going on to tell which of them are going to develop Alzheimer’s and which of them won’t. These scientific breakthroughs are expected to fast-track the discovery of therapies that address Alzheimer’s disease. (source: https://www.newscientist.com/article/2147472-ai-spots-alzheimers-brain-changes-years-before-symptoms-emerge/)
Benefits of AI technology in Alzheimer’s patients
In Alzheimer Detection, specifically detecting the signs of Alzheimer’s early, before the obvious symptoms manifest themselves, could serve a wide variety of useful purposes, such as helping to identify the people who experimental drugs are likeliest to benefit and allowing family members to make arrangements for the care of such patients in advance. The devices that are equipped with the relevant algorithms could easily be installed within the homes of people as well as in long-term care facilities, monitoring those who are at risk. Where patients have already been diagnosed, this technology could aid doctors in making adjustments to their care.
This technology also has applications for drug companies. Drug companies are interested in employing such algorithms to help them monitor patients, searching through them to identify those likely to benefit from being given experimental drugs. AI could also inform investigators whether or not the drugs they are using are addressing the symptoms of the patients.
How it works
Teams of scientists have developed machine-learning algorithms, containing wireless radio signals, capable of analyzing even the minutest of movements, such as breathing. The system is also trained to recognize all simple motions, including falling and walking, as well as more complex movements, such as those related to sleep disturbances. The machine learns the more it is taught, recognizing patterns that human beings would not be able to.
Over a period of time, the device builds large amounts of data readouts, showing behavior patterns. The AI, designed to identify deviations from the set patterns, identifies things like sleep disturbances, depression, and agitation. It also picks up on whether or not a person repeats certain behaviors in the course of the day. All of them are classic symptoms of Alzheimer’s disease.
If the deviations can be caught early, they can be anticipated and managed much more easily.
In practical terms, the technology has been used to detect that an Alzheimer’s patient would wake up at 2am and wander around in her room. It was noticed that she would pace more following the visiting of certain family members. The patient was then given medicine that prevents agitation in response.
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