The primary object of this chapter is to evaluate AI and its application for the Healthcare Industry 4.0. With artificial intelligence, jobs completed by humans are completed faster and at a fraction of the cost, making life easier for patients, physicians, and hospital managers. Artificial intelligence (AI) is used in healthcare in various ways, including discovering new connections between genetic codes, powering robots that assist during surgery, automating administrative work, customizing treatment options, and much more. The numerous contemporary uses of AI in the healthcare industry are examined and discussed. The study focuses on the three newest and most promising areas of AI-powered healthcare: patient care, clinical trials, and AI-led drug development. Time-consuming data monitoring techniques can also be eliminated with the aid of artificial intelligence (AI). large amounts of data may be handled, and highly accurate outcomes can be obtained via AI-assisted clinical trials. Businesses specializing in medical AI provide tools that support patients in all ways. Clinical intelligence also analyzes patients' medical data, offering them insights to help them live better lives. Healthcare 4.0 improves the quality, adaptability, efficiency, and reliability of healthcare delivery by enhancing the patient experience. IoT and intelligent algorithms are all connected and used in healthcare.
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Rising overall healthcare expenditures and a growing shortage of medical specialists are the root reasons for this revolution. Consequently, the healthcare sector is seeking to introduce novel information technology-driven approaches and procedures that have the potential to reduce expenses and address these increasing challenges (Caggianese et al., 2018; Camgoz-Akdağ et al., 2018). Healthcare is moving away from traditional hospitalization care and toward more virtual, distributed care that extensively uses cutting-edge technologies such as AI, DL, home-based healthcare, and robotics. Fundamental changes will affect the healthcare business in the future. Healthcare will be provided as a continuous wellness integration, emphasizing preventive and early intervention rather than the diagnosis goal method. The emergence of intelligent and data-driven technologies has pushed the major shift from traditional medicine to health 4.0. The emergence of the IoT. Healthcare recommendation systems have evolved as a driving force behind offering patient-centered, individualized healthcare services under this umbrella. Recommendation systems are computer programs that make judgments based on accurate input data and important health data obtained by wearable devices, implanted technology, and different sensors. As a result, to comprehend the most recent advancements in the support better (Bhatti et al., 2019; Chung & Kim, 2016). The path from healthcare 1.0 to healthcare 4.0 is examined to identify the technological sectors enabling digitalization. The Overview chapter title is in Figure 1.
The healthcare industry has previously undergone numerous rounds of the technology revolution, beginning with healthcare 1.0, when practitioners physically maintained patient records. Healthcare 2.0 followed, with online technologies replacing paper-based human documentation(Chute & French, 2018; Cui et al., 2020). Healthcare 3.0 has developed to the point where smart devices may now be purchased. Healthcare 4.0 differs from its forebears in allowing many different gadgets to interact with others. Industry 4.0 is a well-known fact that looks to satisfy a wide range of medical demands, with many studies being undertaken in this field. As a result, it's critical to understand how Industry 4.0 may help satisfy various health demands by leveraging technology breakthroughs(Dautov et al., 2019; Kumar et al., 2020). Healthcare professionals are exposed to significant amounts of stress daily. Even in training, doctors and healthcare workers face enormous responsibilities and chronic stress while operating in a competing environment that fosters tension. The fast use of digitalization in healthcare has created massive electronic patient records. The chapter highlights current research problems, outstanding topics, and research perspectives.
AI-supported technologies significantly enhance physicians' diagnostic and treatment decision-making processes by learning and diagnosing from a vast amount of medical research and patient treatment data(Donati et al., 2019; Elhoseny et al., 2018). “AI-based diagnostic algorithms are applied in the detection of breast cancer, serving as a second opinion' in assisting radiologists' image interpretations. It was stated that AI technology can diagnose skin cancer with greater accuracy than a dermatologist with training. (Hathaliya et al., 2019; Khan, Jhanjhi, Omar, et al., 2024). Doctors may soon become obsolete considering these situations, where AI assists or enhances diagnostic, treatment, and operating processes.
The following are the main contributions to this chapter: -