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AI Techniques and IoT Applications Transforming the Future of Healthcare

AI Techniques and IoT Applications Transforming the Future of Healthcare

Vishal Kumar Sahu (Dr. D.Y. Patil Biotechnology and Bioinformatics Institute, Dr. D.Y. Patil Vidyapeeth, Pune, India), Amit Ranjan (Dr. D.Y. Patil Biotechnology and Bioinformatics Institute, Dr. D.Y. Patil Vidyapeeth, Pune, India), Manash K. Paul (Division of Pulmonary and Critical Care Medicine, University of California, Los Angeles, USA), Shuchi Nagar (Dr. D.Y. Patil Biotechnology and Bioinformatics Institute, Dr. D.Y. Patil Vidyapeeth, Pune, India), Shine Devarajan (School of Biotechnology and Bioinformatics, D.Y. Patil University (Deemed), Navi Mumbai, India), Jyotirmoi Aich (School of Biotechnology and Bioinformatics, D.Y. Patil University (Deemed), Navi Mumbai, India), and Soumya Basu (Dr. D.Y. Patil Biotechnology and Bioinformatics Institute, Dr. D.Y. Patil Vidyapeeth, Pune, India)
Copyright: © 2023 |Pages: 24
DOI: 10.4018/978-1-6684-5422-0.ch014
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Abstract

The role of artificial intelligence (AI) has advanced from an analysis and prediction tool to extending human capabilities. Currently, AI is more of a reliable assistant fueled by human experience and need of the hour in the healthcare along with simplifying daily life. AI and Internet of Things (IoT) have opened new avenues in intelligent diagnostics, drug discovery, clinical decision support, enhancing physician-patient communication, transcribing medical documents, and remote treatment. With the advent of enhanced computational power, AI has revolutionized discovery of optimal and efficient healthcare solutions and has accelerated the development of smart solutions involving IoT-based technologies. Starting from telemedicine to predict possible health disorders, AI is gaining focus to facilitate and advance healthcare solutions in developed and underdeveloped countries. This chapter deals with the scope of AI in the present scenario to future developments as AI will soon surpass human and poses threat pertaining to misuse of cognitive sciences development.
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1. Introduction

1.1 Inside the Black Box - Brief of Artificial Intelligence Journey and Advancements

Artificial Intelligence (AI) is competent and excelling by creating new challenges and help developing new technologies. With the increase in the complexity of problems and the upsurge in data generation, AI has emerged as a torchbearer to analyze, interpret, process, and arrange data to extract information and predict future trends in the data. AI is a branch of cognitive sciences concerned with building intelligent machines capable of rationally making logical decisions like living organisms. AI is not a specific domain but an umbrella term covering many technologies and approaches. Typically, there are four types of AI based on the performed tasks: Reactive, Limited memory, Theory of Mind, and Self-aware AI (Korteling et al., 2021) (Davenport & Kalakota, 2019) (Macpherson et al., 2021) (Gill et al., 2022).

1.2 Beginning of AI

John McCarthy and Alan Turing, along with Marvin Minsky, Allen Newell, and Herbert Simon, proposed the famous concept of AI and contributed for around 40 years towards ways to talk to machines (LISP programming language and Garbage Collection method for computer memory management) and making machines think. The idea was developed to answer the question of whether machines can think. What we see today began in 1927, which started with the thought of “Ascribing Mental Qualities to Machines” to make machines capable of problem-solving performance. Although AI proposals suffered a financial crisis, the 21st century is witness to the power of AI in industry, academics, processing, and analysis of big data, and controlling and managing computer hardware (Morgenstern & McIlraith, 2011) (Hoffmann, 2022).

1.3 Adaptation and Development of AI for the Common Man

Following the development of technology and ease of resource manufacturing, AI came to day-to-day life. With the immense increase in information and data generation, the realization turned towards AI as human capabilities seem limited. Though the history of AI dates to the 1950s, earlier development of machine learning algorithms and results were limited for application and adaptation in the field of medicine. With the development of deep learning algorithms in the early 21st century, self-cognitive science started getting integrated into life sciences and healthcare applications. With the availability of substantial medical data, the algorithms are performing well to let humans favor their usage in almost every day-to-day activity of individuals to professional services (Kaul et al., 2020).

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