Parkinson's disease is a progressive nervous system disorder that affects movement and muscle control. Lithuanian researchers from Kaunas University of Technology (KTU) utilized AI to identify the early signs of Parkinson's disease using voice data. The diagnosis of Parkinson's disease has shaken many lives, with over 10 million people currently living with the condition. Although there is no cure, early detection of symptoms can lead to better management of the disease. As the disease progresses, changes in speech can occur alongside other symptoms.

Lithuanian researcher from Kaunas University of Technology (KTU), Rytis Maskeliunas, together with colleagues from the Lithuanian University of Health Sciences (LSMU), tried to identify early symptoms of Parkinson's disease using voice data. Parkinson's disease is usually associated with loss of motor function – hand tremors, muscle stiffness, or balance problems. According to Maskeliunas, a researcher at KTU's Department of Multimedia Engineering, as motor activity decreases, so does the function of the vocal cords, diaphragm, and lungs: "Changes in speech often occur even earlier than motor function disorders, which is why the altered speech might be the first sign of the disease." According to Professor Virgilijus Ulozas, at the Department of Ear, Nose, and Throat at the LSMU Faculty of Medicine, patients with early-stage of Parkinson's disease, might speak in a quieter manner, which can also be monotonous, less expressive, slower, and more fragmented, and this is very difficult to notice by ear. As the disease progresses, hoarseness, stuttering, slurred pronunciation of words, and loss of pauses between words can become more apparent.

Researchers from Kaunas universities in 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.