S.06.03 Cognitive dysfunctions and dementia in Parkinson's disease

Abstract

Computational intelligence (CI) is an emerging field that deals with the design of computer systems replicating the function of the brain. Deep learning is one of the techniques of CI that has gained attention among several learning techniques, since it encapsulates the neural networks with automatic feature extraction stages, in turn resulting in more efficient performance. Health care is a popular research area that extensively utilizes the technique of deep learning in various stages of diagnosis. Alzheimer’s disease (AD) is one of the most challenging diseases, requiring an early and accurate diagnosis in order to extend an effective treatment. Classification of the AD data is the initial and crucial stage in treatment, but this stage is prone to many misclassified cases due to the high degree of similarity within the brain images. This led to the idea of incorporating deep learning in the classification of brain images, since it had attractive results in image classification, even outperforming human skills. The chapter discusses the relevance of deep learning in the diagnosis and treatment of AD. Starting from the concept of CI, the chapter is framed to deliver a clear-cut overview of the technique of deep learning and the benefits of using deep learning in the diagnosis and treatment of AD. Numerous works have been initiated for this purpose and the constantly increasing number of projects in this area illustrates the importance of utilizing CI for AD diagnosis, which is also briefly analyzed in this chapter.