Applications of Deep Learning in Healthcare in the Framework of Industry 5.0

Abstract

Emergence of deep learning (DL) and its applicability motivated researchers and scientists to explore its applications in their fields of expertise. In medical technology, a huge amount of data is required, and dealing with huge data is a challenging task for researchers. The emergence of neural networks and its modifications like convolutional neural networks (CNN), generative adversarial network (AGN), recurrent neural networks (RNN), and their subcategories has provided a stage to flourish deep learning. DL has been a successful tool in the fields of pattern recognition, natural language processing (NLP), image processing, speech recognition, computer vision, etc. All these techniques have been employed in healthcare. Image processing has been proven to be a fruitful technique for physicians to properly diagnose patients through CT scan, MRI, PET, radiography, nuclear medicine, ultrasound, etc. In this chapter, some applications of DL in healthcare have been envisaged, and it has been concluded that this technique is very successful in healthcare.