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Saturday, November 26, 2022

They Build an AI That Detects Parkinson’s Through Breathing

A device developed by the Massachusetts Institute of Technology (MIT) in the United States, along with the presence of a Wi-Fi router, uses a neural network to sense the presence and severity of Parkinson’s, one of the fastest-growing neural networks. It is one of the related diseases. World. World.

Parkinson’s disease is extremely difficult to diagnose because it is based primarily on the presence of motor symptoms such as tremors, stiffness, and slowness, but these symptoms often appear many years after the onset of the disease.

Now, this team of researchers has developed an artificial intelligence model that can detect Parkinson’s by reading a person’s breathing patterns.

The device in question is a neural network, a series of connected algorithms that mimic the functioning of the human brain, capable of assessing whether someone has Parkinson’s by their nocturnal breathing, i.e., breathing patterns that Happens while sleeping.

The neural network is able to understand the severity of someone’s Parkinson’s disease and track the progress of their disease over time.

For years, researchers have investigated the ability to detect Parkinson’s using cerebrospinal fluid and neuroimaging, but such methods are invasive, expensive and require access to specialized medical centers, making them unsuitable for routine testing. which may otherwise provide early diagnosis or continuous monitoring of disease. progress.

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Researchers at MIT showed that an artificial intelligence assessment of Parkinson’s can be done every night at home while a person is asleep and without touching his or her body. To do this, the team developed a device that looks like a home Wi-Fi router, but instead of providing Internet access, the device emits radio signals, analyzing their reflections in the surrounding environment, and draws out the breathing pattern of the subject. Contact Ajay. The breathing signal is fed into a neural network to assess Parkinson’s inactivity, and requires no effort on the part of the patient and caregiver.

“A link between Parkinson’s and breathing was noted as early as 1817 in the work of Dr. James Parkinson. This led us to consider the ability to detect disease by breathing without observing movement. Some medicine Studies have shown that respiratory symptoms appear years before motor symptoms, which means that breathing features may hold promise for risk assessment prior to the diagnosis of Parkinson’s,” says Dina Katabi, one of the leaders of the research. Which is published in the scientific journal ‘Nature Medicine’.

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The fastest growing neurological disease in the world, Parkinson’s is the second most common neurological disorder after Alzheimer’s disease. In the United States alone, it affects more than a million people and has an annual economic burden of $51.9 billion. The research team’s algorithm was tested on 7,687 individuals, including 757 Parkinson’s patients.

Katabi notes that the study has important implications for drug development and clinical care for Parkinson’s. “In terms of drug development, the results could enable clinical trials with significantly shorter durations and fewer participants, ultimately accelerating the development of new therapies. In the context of clinical care, the approach may aid in the evaluation of patients.” Under-served communities, including those with Parkinson’s traditionally living in rural areas and having difficulty leaving home due to limited mobility or cognitive decline,” he says.

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