Scientists from the St. Petersburg State Electrotechnical University “LETI” have developed an innovative algorithm based on a neural network that can identify possible signs of cognitive disorders, including Parkinson’s disease, from a photo of a spiral drawn by a patient. This groundbreaking method could change the approach to early diagnosis, the university reported.
Parkinson’s disease is a complex neurodegenerative disease that begins in adults between the ages of 30 and 50. It gradually destroys brain cells, causing slow movements, tremors, and other symptoms. It is difficult to diagnose the disease before obvious symptoms appear, and early diagnosis is critical to slowing the progression of the disease. It is currently estimated that approximately 10 million people worldwide suffer from the disease.
LETI’s new algorithm offers an innovative solution: it analyzes a photo of a patient’s spiral drawing and identifies possible deviations associated with cognitive impairment. The neural network processes the image and can detect signs of the disease that were previously assessed only by the doctor’s subjective opinion. As the author of the project, Ekaterina Syrtsova, notes, this technology could become the basis of medical programs and help patients monitor their condition. Testing of the model showed an accuracy of 99.3%, which opens up new opportunities for rapid diagnosis of neurodegenerative diseases.
Source: Ferra
I am a professional journalist and content creator with extensive experience writing for news websites. I currently work as an author at Gadget Onus, where I specialize in covering hot news topics. My written pieces have been published on some of the biggest media outlets around the world, including The Guardian and BBC News.
