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Parkinson's disease (PD) is currently one of the fastest growing diseases in the world and is the second most common neurological disorder
In a new study published in Nature Medicine on Aug.
Over the years, researchers in the field have identified a number of potential Parkinson's disease biomarkers, such as cerebrospinal fluid, blood biochemistry and neuroimaging have good detection potential
As early as 1817, the discoverer of Parkinson's disease, the British physician James Parkinson, noticed the relationship between
In the new study, the team developed a new AI-based neural network model for detecting Parkinson's disease, predicting disease severity, and using nighttime breathing ( that is, breathing characteristics during sleep ) to track the progression
In addition, in order for the system to be performed every night while sleeping at home without touching the subject's body, the team developed a device that looks like a home Wi-Fi router, but instead provides internet access, but instead emits radio signals, analyzing their reflections to the surrounding environment to extract the subject's breathing characteristics
An important component of the model design is that it learns from nocturnal breathing the auxiliary task of predicting a person's quantitative electroencephalogram (qEEG), which prevents the model from over-quasi-merging to help interpret the model's output information
Study co-author Professor Ray Dorsey, a neuroscientist at the University of Rochester and a Parkinson's disease specialist, said: "We have not made any breakthroughs in the treatment of Parkinson's disease this century, which shows that our current approach to evaluating new therapies is not ideal
The average cost and time of Drug Development in Parkinson's is about $1.
With preliminary evidence so far, the system can be used for risk assessment
Taken together, this study suggests that advances in AI can support medical advances
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