Comparison and Analysis of the Use of Advanced Methods of Artificial Intelligence for Neurodegenerative Diseases

Abstract

The paper deals with the comparison of existing methods of using artificial intelligence (AI) for the effective diagnosis of selected neurodegenerative diseases. The use of AI for disease diagnosis has advanced significantly in the last decade, as well as the use of various machine learning methods of speech recognition for disease diagnosis. The use of new technologies based on AI can help find a solution to a non-invasive, easy-to-apply method for detection and subsequent treatment of brain diseases. Diagnosis of neurodegenerative diseases has mainly been performed using neuroimaging methods such as magnetic resonance imaging or positron emission tomography or single-photon emission computed tomography. The aim was to analyse existing AI-assisted diagnostic approaches based on peer-reviewed publications and to highlight current trends in the diagnosis of Alzheimer's and Parkinson's diseases. Finally, we showed our approach to early diagnosis of neurodegenerative diseases.