- Researchers built an algorithm to predict Parkinson’s disease from short speech samples.
- Their model was able to predict 80-90% of Parkinson’s disease cases.
- They are now developing their algorithm into an app to help identify those at risk of the condition.
Parkinson’s disease (PD) is the
The
Currently, PD diagnoses happen late in the neurodegenerative process. Earlier identification of symptoms could allow for earlier intervention and thus longer uncompromised working capacity and prolonged quality of life.
Speech acoustic analysis in PD has received growing scientific interest in recent years as a potential diagnostic biomarker. Studies have
Further understanding how PD affects the voice could lead to the development of screening methods that can distinguish between the voices of PD patients and healthy individuals.
Recently, researchers developed an automated screening method that can distinguish between the voices of PD patients and healthy individuals.
The researchers found their model could predict 80-90% of voices from those with PD.
“The goal of making a Parkinson’s diagnosis easy is admirable,” Dr. Clifford Segil, a neurologist at Providence Saint John’s Health Center in Santa Monica, California, who was not involved in the study, told Medical News Today.
“There are not enough general neurologists or movement disorder neurologists in the world at this time. I agree with the authors that this study is not meant to be a substitute for a…
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