ABSTRACT
With the use of artificial intelligence (AI) and one of its branches (i.e., deep learning), computer scientists and healthcare professionals aim to bring a new paradigm shift in the healthcare industry. AI refers to the ability of a machine to emulate and impersonate the cognitive intelligence of a human being like problem-solving, pattern-detection, and strategic thinking. Since its introduction in 1956 at a conference at Dartmouth, UK, there has been significant development in the field of AI which has thus resulted in pioneering of new intelligent software and machines which are able to perform complex tasks equivalent to humans, and in few instances, surpassing them even. With the increasing availability of healthcare data, medical records, and rapid progress in analytical abilities of the software, AI applications can perform critical healthcare tasks, such as diagnosis, treatment, and further disease prevention. In this chapter, we study how AI is gradually changing conventional medical practices by considering the case of glaucoma, the leading cause of blindness worldwide. We demonstrate how systems based on convolutional neural networks (CNN) trained with optical coherence tomography (OCT) scans and digital fundus images can distinguish between healthy and glaucomatous patterns with high accuracy and correlate it with traditional diagnosis.
