Advancements in Deep Learning for Early Detection and Diagnosis Across Multiple Disease Domains
Abstract
Identification and diagnosis of diseases in its early stages is one of the biggest determinants of improving patient health and needs, as well as decreasing general health care costs. Hence, with the application of deep learning, there has been a total change in the methods of medical diagnosis. This scoping review provides an employment of the current research progress of deep learning in different disease types, such as cancer, neurodegenerative diseases, and ophthalmologic diseases. This paper intends to compare different deep learning architectures, preprocessing methodologies used for data, and how data is incorporated into the framework, with a view of giving a glimpse of what researchers are currently doing in this fast-growing field, difficulties that are being encountered, as well as the future direction of the research domain being considered in this paper.