Artificial Intelligence (AI) for IoHT – An Introduction
Artificial Intelligence (AI) in the Healthcare Domain
Presently, there is a need for a model with its linked gadgets, persons, and networks completely integrated on the Internet of Health Things (IoHT), which offers medicinal services to patients, monitoring patients, and offering drug recommendations. The IoHT incorporates both technological expertise and electronics. Artificial intelligence (Al) is the application of science-based research and the development of smart machines. The people without the knowledge of intelligent machines conjure images of charismatic human-based systems and robots, as depicted in science fiction . The most familiar media reports of applying aerial surveillance drones, driverless cars, and other features of perils in emerging smart machines, which has been improved with common awareness. Al models and approaches are predefined from other formulations. Several domains of Al schemes are available in the literature .
Al models are applied in automobiles, aircraft guidance fields, smartphone equipment like audio analysis applications such as Apple’s Siri. Internet web browsers, and a plethora of alternate practical actions. Al methodologies tend to resolve problems and perform events in stable, effective, and productive types when compared with other possibilities. The nature of mental healthcare domains provides the merits and advancements in Al . For instance, processing models to learning, understanding, and reasoning helps the experts in clinical decision-making, analysis, diagnostics, and so on. Al approaches could be more advanced in self-care devices to enhance people’s lifestyles, such as communicative mobile health fields that know the patterns as well as priorities of customers. Al results in the enhancement of public health under the assistance of detecting health risks and data inventions. An alternate instance of Al is that virtual humans are capable of communicating with care seekers and can give appropriate remedies to cure the disease. This chapter depicts the chance of applying Al models and methods for healthcare operations in future advancements [4, 5].
The main objective of Al is to develop machines with the potential to perform tasks such as essential intelligence, like reasoning, learning, planning, problem resolving, as well as perception. The relevant fields involved in Al are shown in Fig. 1.1. This domain was named by computer scientist John McCarty, and Marvin Minsky, Nathan Rochester, and Claude Shannon implied it at the Dartmouth Conference. The key objective of this conference was to set a novel domain of science that contributes to the study of modern devices. Each perception of learning intelligence could be so precisely defined that a machine is made to develop it. At
FIGURE 1.1 Relevant fields of AI.
the time of the conference, Allen Newell, J.C. Shaw, and Herbert Simon illustrated the Logic Theorist (LT), as the initial computer program manufactured to reflect problem resolving techniques .
In the last few decades, AI has been developed into multidisciplinary fields with computer science, engineering, psychology, and so on. Few objectives can be accomplished by the application of AI. to develop a framework to achieve remarkable events such as computer vision, audio recognition, and detection of patterns that exist in data . It mainly concentrates on specialized intelligent actions that have been named as Weak AI, also termed as Applied AI. Instead of thinking that humans can play chess. Deep Blue employs the application of brute force approaches to estimate the possibilities to compute the offensive as well as defensive movements. The term “Strong AI” was coined by philosopher John Searle in 1980, and defines the aim of deploying machines with common AI. The major intention of Strong AI is to deploy machines with smart capability that is indistinguishable from humans. Such resources are typically narrow and accurate tasks, namely the function of arithmetic task. AI is utilized to invent the intelligent nature of machines to perform the events of human behavior. AI might be the form of either hardware or software that can stand alone, distributed over the computer networks, or embedded into a robot. Besides, it is in the form of intelligent and independent agents that are capable of communicating with the corresponding platform in the decision-making process. AI is combined with biological operations for brain computer interfaces
(BCIs), which is manufactured with biological objectives (biological AI), and small molecular structures referred to as nanotechnology .
Several clinical decision support systems (CDSSs) were presented by the use of AI approaches and finds useful in several domains . This chapter offers an introductory explanation of AI concepts, evolution, clinical data generation, and AI techniques in healthcare. This chapter also discusses several applications of AI techniques developed in the healthcare sector.