Deep Neural Networks for Early Diagnosis of Neurodegenerative Diseases

Abstract

Early diagnosis of neurodegenerative diseases plays a remarkable role in providing timely treatment for the affected person and reduces the mortality rate. Neurodegenerative diseases can affect the mental and physical health of a person and can impact decision-making. Deep neural networks help in automating disease diagnosis by identifying biomarkers from complex patterns of a large dataset. This chapter discusses the impact of using deep neural networks in neurodegenerative disease diagnosis. The initial section of the chapter focuses on the basics of neurodegenerative diseases and their impact on the well-being of the individual. The chapter also outlines the importance of transfer learning and multimodal fusion in early disease diagnosis. Finally, the chapter explores ethical considerations to be followed during the deployment of a deep learning model used in prediction of neurodegenerative disease. Thus, this chapter provides a remarkable role of deep learning architectures in neurodegenerative disease diagnosis.