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Applied Smart Health Care Informatics


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acquisition of high quality images and their storage from the many screens associated with every patient (Belle et al., 2015). Physiological signals not only create information dimension problems but also have baffling complexity of a spatiotemporal nature. Nowadays, numerous heterogeneous and uninterrupted monitoring devices are employed in the health care system to apply solitary physiological waveform information or crucial discrete data provided to systems if there should be an occurrence of plain occasion (Cvach, 2012; Drew et al., 2014).

      The human genome is comprised of about thirty thousand genes. It has been observed that the price to sequence the human genome decreases with the advancement of high‐throughput sequencing technology (E.S. Lander and et al., 2001; Drmanac et al., 2010). Investigating genome‐scale information with suggestions for current public fitness insurance policies, the conveyance of care, and creating noteworthy proposals in an opportune way is a sizeable undertaking to the discipline of computational biology (Caulfield et al., 2013; Dewey et al., 2014). In a clinical setting, the delivery of these recommendations are very costly as time is very crucial.

      Artificial intelligence impacts the health care domain as AI is the development of computer systems able to perform tasks that requires human intellect. Tasks such as object detection, decision making, solving complex problems, and so on are a few main benefits of artificial intelligence. AI also gives us predictions with an increased level of accuracy, it helps in decision making processes, it has solved complex problems, and it quickly performs high‐level computations that take days for a human to solve. AI is something that makes human lives easier by performing high level computations and solving complex problems.

      According to the PricewaterhouseCoopers (PwC) report, artificial intelligence will contribute an additional $ 15.7 trillion to the world economy by 2030, and the greatest impact will be in the health care sector (pwc). Healthcare is getting more import and using AI in more advanced manner. The sudden importance of AI in the health care industry can be categorized into two major points. First, the high availability of medical data; many of us have tons and tons of medical data in the form of our medical history and the availability of data makes implementing artificial intelligence much easier (Bush, 2018). Second, the introduction of complex algorithms. Machine learning alone is not capable of handling high dimensionality data and medical histories are extremely high dimensional in character, there are thousands of attributes that are hard for humans to analyze and process data through machine learning. However, when neural networks and deep learning were introduced, the process become much easier. Neural networks and deep learning are focused on solving complex problems that involve high dimensionality data; their development played a significant role in the impact of AI on health care (Simon et al., 2007; Loria).

      AI benefits health care organizations by implementing cognitive technology to unwind a huge amount of medical records and perform power diagnosis. For instance, Nuance is a production service provider that uses artificial intelligence and machine learning to predict the intent of a particular user. By implementing Nuance in organization system to develop a personalized user experience, a company can make better actions that enhance customer experience and overall benefit the organization. Nuance helps in the storing, collecting, and reformatting of data to provide faster and more consistent access to allow further analysis or diagnosis. These are examples of how AI is gaining attention and being helpful to the health care industry (Aronson and Rehm, 2015; Schmidt‐Erfurth et al., 2018).

      Cloud Computing is significant in the health care sector as it supports big data analytics that are being used to improve decision support systems and contribute to therapeutic strategies in beneficial ways.

      Smart health care informatics involve the combined use of the IoT, big data analytics,cloud computing, and artificial intelligence. These technologies will be made of use in health care by the application of artificial intelligence to examine and fit a giant quantity of data to screen for exclusion standards and decide the most appropriate objectives, keeping the time of recruiting the topics, and enhancing the concentrated efforts on the goal population. Further, patients are supervised in actual time with the usage of smart wearable devices to acquire extra time‐sensitive and correct information, for instance, the practice of smart devices to display data in lung ailment clinical trials. Using big data analytics and synthetic genius in the field of health care research and the improvement of drugs will grow to be of greater convenience. The arrival of smart health care, mature standards, and structures has been organized. However, with the upcoming modern technologies, there is a huge scope for development, and many challenges are now coming out.

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