Neurological Disorder Classification using Convolutional Neural Networks - Jadhav, Amolkumar N.; Chavan, Sandip B.; Patil, Ajit R.; Khatawkar, Shrihari D.; Nalavade, Jagannath E. (International Journal of Intelligent Systems and Applications in Engineering, 2024)
The rapid development of neuroimaging techniques has led to the emergence of the study of brain illness identification as a new area of study in the deep learning community. Research on deep learning faces various unique challenges due of data on brain illnesses. There are usually other clinical metrics available that show the sickness status from different perspectives. Complementary data from the tensor and brain network data, along with other clinical characteristics, are anticipated to help us better understand illness causes and direct treatment interventions. They have excelled in a number of applications, including multi view feature analysis, sub graph modelling, and tensor-based modelling. In this study, we examine several recent deep learning techniques for brain illness analysis.