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Each year, more than 60,000 Americans are newlyDiagnosed with Parkinson's disease (PD) - And this number increases rapidly. In fact, according to the World Health Organization, the prevalence of the neurological disorder hasdoubled in the past 25 years, and the disability and death -related deaths are "increasing more quickly than for any other neurological disorder".

Unfortunately, the path to aDiagnosis of Parkinson Maybe long and difficult due to a lack of diagnostic tests. This is why a group of researchers from the Massachusetts Institute of Technology (MIT) explores new ways of detecting the PD by examining the way you breathe. Read the rest to find out more about the surprising link between your night breathing models and the risk of your Parkinson - and to discover how the artificial intelligence of the test advances the field.

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Parkinson's disease is a progressive disorder, which means that it worsens over time. Most often, it is not diagnosed untilCommon motor symptoms- Tremor, rigidity, waterproofing or imbalance, for example - for example. However, experts are increasingly examining less common clinical manifestations of the MP - as well as possible biomarkers - which could help drive earlier.

"Atrue determination of Parkinson's disease is a clinical diagnosis, which means that certain motor symptoms should be present, but we now know more on certain early signs of Parkinson's disease which, although they do not always lead to the disease, are connected ", the Experts from Johns Hopkins University wrote.

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According to a new study by MIT experts and published in the journalNature Medicine, there is a surprising link betweenThe way you stay at night And your risk of Parkinson's disease.

"A relationship betweenParkinson and breathing was noted in 1817, in the work of Dr. James Parkinson. This motivated us to consider the detection potential of the disease of his breathing without looking at the movements "Dina Katabi, PHD, professor of electrical and computer engineering (EECS) at MITNews put. "Some medical studies have shown that respiratory symptoms are manifested years before motor symptoms, which means that respiratory attributes could be promising risks before the diagnosis of Parkinson."

The researchers collected data on the night respiratory schemes of 7,600 people, 757 of whom had known cases of Parkinson's disease. They then tested the capacity of a computer model based on artificial intelligence to diagnose and follow the PD. They found that when they followed the breathing of the subjects for a period of 12 nights, the program could detect the Parkinson with 95%precision.

The test, which could one day be administered in the comfort of his house, consists of two key components: a belt worn by the patient at night and a device that emits radio signals to collect data on the patient's breathing models . "The system extracts nocturnal respiratory signals either from a respiratory belt carried by the subject, or radio signals which bounce from their bodies during their sleep. It processes the respiratory signals using a network of neurons to deduce if the person has a PD, and if they do, assesses the gravity of their PD, "said the authors of the study.

Researchers say that their results could be among the best means ofdetect parkinson through biomarkers. "The literature has studied some potential PD biomarkers, including cerebrospinal fluid, biochemical blood and neuroimperie have good precision. However, these biomarkers are expensive, invasive and require access to specialized medical centers and, therefore, Not suitable for frequent tests to provide early diagnosis or continuous monitoring of the progression of the disease, "they wrote.

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In addition to providing new pathways to diagnosis, researchers say that their test technology could also help detect changes in the progression of the disease over time. "The scales currently used to measure the progression of the disease in the clinic are relatively insensitive. They can also provide different results when used by different doctors. Compared to two different scales, the program was better to identify small Changes in Parkinson's symptoms, "said the team.

They added that their results could help accelerate clinical trials, ultimately leading to faster development of new therapies. "In terms of clinical care, the approach can help the evaluation ofParkinson patients In traditionally unprecedented communities, including those who live in rural areas and those who find it difficult to leave the house due to limited mobility or cognitive impairment, "said Katabi.

It is important to note that more research is necessary to determine the effectiveness of AI algorithms in clinical areas. ""We need more data, "Katabi recognized by speaking toThe Washington Post in September. "We have just started to produce these results, and we need more evidence."