A TECHNICAL SURVEY ON IDENTIFICATION AND DIAGNOSIS OF DISEASES USING DEEP LEARNING

This article provides a comprehensive review of recent developments in deep learning, including both its theoretical underpinnings and its innovative practical applications. This article provides a historical overview of the significant uses of deep learning algorithms. Comparing the deep learning approach with more traditional algorithms, this article highlights the method's advantages and benefits. This includes the deep learning approach's layer-based hierarchy and nonlinear operations. The state-of the-art review also gives a high-level explanation of deep learning's advantages and growth in popularity. With deep learning, meaningful hierarchical linkages within the data can be discovered algorithmically without the need for painstaking hand-crafting of features, which is especially useful in the era of medical big data. We discuss the state-of-the-art in medical picture segmentation, localization, detection, and registration, as well as its most important applications.