Researchers from Kaunas universities, Lithuania developed a deep learning-based method that can predict the possible onset of Alzheimer’s disease from brain images with an accuracy of over 99 per cent. The method was developed while analysing functional MRI images obtained from 138 subjects and performed better in terms of accuracy, sensitivity and specificity than previously developed methods.
According to World Health Organisation, Alzheimer’s disease is the most frequent cause of dementia, contributing to up to 70 per cent of dementia cases. Worldwide, approximately 24 million people are affected, and this number is expected to double every 20 years. Owing to societal ageing, the disease will become a costly public health burden in the years to come.
“Medical professionals all over the world attempt to raise awareness of an early Alzheimer’s diagnosis, which provides the affected with a better chance of benefiting from treatment. This was one of the most important issues for choosing a topic for Modupe Odusami, a PhD student from Nigeria,” says Rytis Maskelinas, a researcher at the Department of Multimedia Engineering, Faculty of Informatics, Kaunas University of Technology (KTU), Odusami’s PhD supervisor.
https://t.co/RIND7DrWRE Predicting possible Alzheimer’s with nearly 100 percent accuracy. The method was developed while analyzing functional MRI images obtained from 138 subjects and performed better in terms of accuracy, sensitivity and specificity than previously developed m… pic.twitter.com/uI1UeItWdF
— Science news (@UpdateonScience) September 8, 2021