Artificial Intelligence Challenges, Principles, and Applications in Smart Healthcare Systems

Abstract

Introduction: Artificial intelligence (AI) is a term that refers to the use of technology to create intelligent computers that can perform activities and behaviors similar to those of humans. In 1956, John McCarthy coined the phrase “artificial intelligence” to characterize the process of creating intelligent robots. AI has the potential to revolutionize medicine, but its practical applications are still in their infancy, requiring more research and development. AI in healthcare is increasingly becoming a part of the business, with numerous interesting applications being investigated in a variety of medical fields. The advantages and disadvantages of using artificial intelligence in healthcare are discussed in this article. Various variables, such as logistical obstacles, cultural hurdles, and the requirement for follow-up research and training, all contribute to the difficulty of adopting AI systems in healthcare. There are also some recommendations for determining the viability of AI systems in the healthcare field. The most clinically relevant performance measures should be captured, and they should be intelligible to the intended consumers. There is a need for direct comparisons between AI systems and those created by humans. The different hazards connected with the creation of AI algorithms must also be considered by developers.Conclusion: It's difficult to translate AI research into clinical practice since it necessitates the development of reliable evaluation techniques that are both accurate and simple to apply. More research is needed to create methods and procedures that make machine learning predictions more understandable.

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