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INTRODUCTION
Artificial intelligence (AI) has received a lot of attention in recent years, and it has evolved into one of the main drivers of not only modern life (via Siri, Alexa, using Google, etc.), but also medicine.
Artificial intelligence (AI) is a branch of science and engineering concerned with the computational under-standing of what is commonly referred to as intelligence, as well as the creation of objects (machines) that exhibit such behavior (computer programs). Actually AI is a conceptual term denoting a series of basic technologies that enable digital systems or computers to perform functions involving human-like intelligence. It allows humans to combine human intelligence with computer technology to serve better.2
Machine learning is an artificial intelligence that enables computer systems to learn directly from exam-ples, data, and experience.
Background
Alan posed the question “Can a machine think?” in 1950, and proposed a test for machine intelligence - later known as the Turing Test - in which a machine would be considered intelligent if its responses to ques-tions could help convince a human. In 1952, Arthur Samuel created an early learning machine that could learn to play chess by using annotated guides written by human experts and then played itself to learn and distinguish between good and bad moves. (3)
John McCarthy, a computer scientist, invented the term “artificial intelligence” in 1956. (4) . Hinton et al. developed deep learning and convolutional neural net-works (CNNs), which were presented at the ImageNet Large-Scale Visual Recognition Challenge in 2012 (3).
The science which makes machines intelligent is artificial intelligence (AI) and Machine learning is a technology that empowers computers to execute specific tasks once it learns from examples. As a result, rather than following pre-programmed rules, these systems can learn from data and execute complicated operations. Significant advances in machine learning capabilities have occurred in recent years due to technological ad-vancements, with increased data availability, and high computing capacity. With these advancements, systems that were unable to achieve precise results previously, now perform certain tasks better than humans. Systems for object recognition and voice are now more effective than human beings at some tasks.
In comparison to traditional programming methods, ML can learn from data, to perform different compli-cated tasks. The fields of computer science, statistics, and...