Evolution of Artificial Intelligence and Deep Learning in Healthcare

Abstract

The imitation of human intelligence by computers, primarily computer systems, is known as artificial intelligence (AI). Sophisticated computers can simulate cognitive abilities such as memory, remembering, problemsolving, and decision-making that are linked with the human brain. Deep learning (DL) is a more specialized extension of AI that allows systems to group data and make forecasts with greater accuracy while requiring less human intervention. A neural network with three or even more layers is used in DL. These neural networks aim to imitate the human brain’s cognitive skills better, allowing it to process and learn from bigger volumes of data. While we are still a long way from replicating the human brain, DL is a positive step forward. Take, for instance, a self-driving vehicle. Consequently, AI approaches have made big ripples in the healthcare field, creating a heated discussion on whether AI physicians may eventually replace human doctors. Human doctors, we think, will not be substituted by automation in the near future, but AI will surely aid physicians in making better clinical judgments, and in some areas of healthcare, AI may entirely replace judgment. The widespread availability of healthcare data and the rapid development of big data analysis techniques have made current practical applications of healthcare analytics possible. When 168driven by clinical research queries, powerful AI algorithms may disclose clinically essential information buried in enormous volumes of data, which can improve clinical decision-making. The chapter highlights the role of AI in healthcare. The chapter will also enlighten the readers about the research scope of DL in Healthcare. The chapter will be helpful for AI and DL enthusiasts, healthcare professionals, PhD scholars, researchers, and students.

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