The evolution of these technologies has opened new opportunities and possibilities in the field of healthcare. Armando observed the adoption of smart healthcare monitoring devices in India and pointed out that the cost varies according to the features and design of the device. Despite this it is investigated how these devices can have a remarkable effect in developing countries that have reduced treatment cost and patient time at the same level [5].
The rising trend of remote healthcare allows for a timelier administration of treatment for patients at their homes, significantly reducing the cost of intervention as well as improving the quality of care with personalized technologies. The patients can decide whether or not to further consult healthcare professionals. The automated computational readings of smart devices refer consultation of a physician to seek emotional support and inpatient care. For personalized care, patients may also use applications to detect a correspondence between the condition and medication interactions to make the decisions on how to improve their health. Furthermore, for more in‐depth testing, patients may also decide to use home kits or personalized genomic services. Smart healthcare technology consists of different components such as sensors, smart pills, smart surgeries, wearables, and registration devices. Remote technologies may help healthcare professionals to provide fast and better care.
Technologies such as cloud computing, artificial intelligence (AI), 3D printing, Internet of Things (IoT), 5G, and blockchain revolutionized our physical world by doing a digital replacement of real‐world objects with virtual ones. In this chapter, we discuss the role of emergent technologies (such as AI and blockchain), their usage, and applications in smart healthcare. AI is leveraged to make predictions based on the learned patterns and experience of the machines. 5G is another emerging technology, which is currently in its commercialization phase. Similarly, blockchain, a distributed ledger, is used for data and transaction transparency as well as immutability. Once the data has been recorded in the blockchain, it becomes immutable. Shou [1] indicated that the problems of existing smart healthcare are not only dependent on technological advancement but also a joint venture of doctors, patients, and health institutions related to cost reduction, management of diagnostics and data, which improves patients’ feedback. Yin et al. [6] discuss implantable and wearable medical devices that gather physical signals from anywhere and anytime, which are based on IoT and machine learning. The world is facing numerous health crises in case of surgeries, treatments, and ever‐increasing demands of medicines, but all of these crises will be tackled by the emergence of smart care technologies in the health sector.
1.2 Emerging Technologies in Smart Healthcare
Several technologies are revolutionizing the field of healthcare, from the process of diagnosis until final treatment. At this stage, the role of technology is becoming prominent. The Working Party on Biotechnology, Nanotechnology, and Converging Technologies (BNCT) recommends policies for managing emerging technologies for health innovation, converging technologies, and norms of good governance of healthcare [9]. To get healthy it is necessary to receive better results, and there should be an association between patient and doctor for healthier treatments. Treating patients is itself a task, and this task would be done properly by a quality collaboration of patients and healthcare professionals. Misha described a methodological review over the healthcare transformation that showed how computational methods and simulation made a base for evolution in healthcare by facilitating physiological measurement to detect organic systems [7]. Information technology is a world‐class example in this field together with biomedical equipment to establish the keystone of smart healthcare.
OECD (Organisation for Economic Co‐operation and Development) countries Science and Technology Scoreboard [8].
Figure 1.1 is a science, technology, and innovation scoreboard in the field of research and development with continuous evolution and enhances data visualization tools. The graph is derived from the OECD (Organisation for Economic Co‐operation and Development) database, indicates technological advancement from 2005 to 2019 in China, the European Union, Japan, Korea, and OECD countries, and it indicates Korea became more diverse from 2005 to 2019. The scoreboard contained the indicator of gross domestic expenditure on research and development as a percentage of GDP (Gross Domestic Product) for the countries mentioned in the graph.
Figure 1.1 OECD countries, science and technology.
1.2.1 Artificial Intelligence (AI) in Healthcare
AI holds great sovereignty in the field of computer technology and is spreading its autonomy among many sectors of the world. One of the main sectors influenced by AI is healthcare as it digitizes human life at a vast level from the life of a single individual to several people’s lives. AI is having a great impact on economical, societal, and industrial domains through healthcare and medicine. Some of the roles we define in this chapter such as AI can anticipate the current heart rate of an individual using big data machine learning and expert systems. Another benefit anticipated is that it has made medical care less costly and more available. AI has made it simple for doctors, nurses, and hospital staff to do complex jobs in a very short time and in an efficient manner.
Going through the important medical questions, AI techniques can compile healthcare information from big data sources, which helps in proper decision‐making converting these several pen‐and‐paper‐based processes into a digitized form to make computer software more intelligent and autonomous. AI and machine learning are accelerating the cadence of healthcare very quickly. AI aims to recast the medical industry and bring about certain strategies that were unattainable in real scenarios. AI helps analyze and identify patterns in ambiguous datasets more quickly and efficiently. On the other hand, machine learning makes use of learning algorithms to extract attributes from the incoming data (input data is the patients’ attributes such as gender, medical history, genetic expression, age, analytical imaging, and symptoms). The OECD AI Principles are the first such principles signed up to by governments. Beyond OECD members, other countries including Argentina, Brazil, Costa Rica, Malta, Peru, Romania, and Ukraine have already adhered to the AI Principles, with further adherents welcomed.
The role of AI is to make computers more beneficial in overcoming healthcare challenges. Various chronic diseases such as diabetes, Alzheimer’s, several types of cancers including colon and breast cancer, and cardiovascular diseases are diagnosed early just due to AI.
The recommendation indicates five complementary