The Role of AI in Revolutionizing Healthcare Systems

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THESIS WORK
Role of artificial intelligence in Health care
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Chapter 1-Introduction

Background study
AI stands for Artificial Intelligence. It can be defined as the human intelligence simulations that
are further processed by machines. The machines that stimulate human intelligence are generally
computers (Ghahramani, 2015). Artificial intelligence includes learning and gaining useful
information. It also helps in reasoning and the rules of self-correction. Categorization of artificial
intelligence can be done as weak AI and strong AI. A weak artificial intelligence can be defined
as artificial intelligence that is designed for a particular task. There is a strong artificial
intelligence system that can be used in unfamiliar tasks. All the unfamiliar tasks can be
accomplished without the intervention of human (Hassabis, et. al., 2017). There are various
examples of Artificial learning which are given below:
Automation: When a system is made to work automatically, it is known as automation. High
volume tasks can be repeatedly performed by the automation in the systems. It makes the
tasks of humans easier.
Machine leaning: When a computer is made to act automatically without any use of
programming, it is called machine learning. Deep learning can be said to be a subdivision of
machine learning. Machine learning can be also be divided into three subparts as supervised
learning, unsupervised learning and reinforcement learning.
Machine vision: The machine vision is an example of machine vision that captures the visual
information by the use of cameras and then analyzes the visual information by converting it
from analog to digital signals (Gunning, 2017).
Natural language processing: The natural language program can be referred to as the
processing of human language by the use of computer programs.
Robotics: As technology is increasing day by day, works are done by robots. Robotics is an
artificial intelligence form in which designing and manufacturing of robots are done. Robots
are used to perform those tasks that are difficult to be performed by humans.
Applications of Artificial intelligence
Artificial intelligence in health care: The application of artificial intelligence in healthcare is
done to reduce the costs incurred by the patents and also to improve the quality of treatment
provided to the patients (Moravčík, et. al., 2017). Artificial intelligence systems in health are
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designed to analyze and mine the data of the patients and develop a hypothesis which is
afterwards presented as a score. Artificial intelligence also takes a form of a chat form in the
healthcare industry, which is used for online questions and answers so that the customers can
be assisted. The systems are also used for a virtual assistance for maintaining health. The
payment of bills and booking of appointments are also made by the artificial intelligence
systems (Jiang, et. al., 2017).
AI in business: The algorithms for machine learnings are used to develop such systems that
can perform difficult and repetitive tasks in the business. It is done to serve the customers
better and analyze the business condition so that effective decisions for the business can be
taken by the management of the business.
AI in education: The system of artificial intelligence can be also be used in the education
sector as it helps in giving grades and provide educators with more time to invest in other
productive things. AI can be used in the education sector as it is capable of assessing the
needs of the students and track their performance. The way of students learning can be
changed by artificial intelligence.
AI in Finance: Artificial intelligence is also used in financial institutions. The system is able
to collect the personal data of the customers and track their history, which makes it easier for
the financial institutions to provide effective financial services.
AI in manufacturing: Industries use robots in manufacturing areas. They perform those tasks
which cannot be easily performed by humans. So robots can be effectively used to perform
those tasks and make manufacturing easy.
Artificial intelligence in healthcare
This study is aimed at analyzing the use of artificial intelligence in the healthcare sector. The
artificial intelligence in the healthcare system makes use of complex algorithms and software so
that the human cognition can be estimated. The complicated medical data can be easily analyzed
by the use of an artificial intelligence system. The artificial intelligence systems in health care
can provide effective output without the direct intervention of humans. The artificial intelligence
systems in the healthcare industry can process the data and provide feedback to the end users
(Yu, et. al., 2018).
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The major use of artificial technology in healthcare is done to establish a relationship between
the treatment and prevention techniques that can be used for the effective treatment of the
patients. The use of artificial intelligence in the field of healthcare helps in power computing so
that the data can be collected and processed faster. The volume of healthcare related data can be
increased by the use of artificial intelligence systems. The genomic sequencing data base is also
used to track the health record of the patients, which is very advantageous in providing treatment
to the patients. Healthcare record systems are utilized to record large data related to the health
and medication of the patients. The human perpetual processes can be replicated by the
application of natural language processing. The robot-assisted surgery is also a new application
of artificial intelligence.
Aims and objectives
Every research is carried out to attain some objectives. This is research that is based on the
application of artificial intelligence in the area of health care. The research is aimed at the
analysis of the ways by which artificial intelligence can improve the health care systems. It will
also be analyzed by the research of how the artificial, intelligence systems can be used for faster
diagnosis and treatment of the patients. There are certain barriers in the healthcare system which
prevents the doctors in providing effective treatment to the patients so this research will help to
gain knowledge about the ways by which these barriers can be removed so that timely and
effective treatment can be provided to the patients. The main aim of the research is to find out
about the utilization of artificial intelligence in the UK health care industry. The laws and
regulations that are required for the incorporation of artificial intelligence in the UK health care
will also be reviewed in this investigation.
The research has certain objectives that are enumerated below:
Analyze the previous research papers and articles to use in this study.
To analyze the areas in which artificial intelligence is already successful.
To get the study trends related to the incorporation of artificial intelligence in the UK health
care system.
To carry out a proper survey to know about the effectiveness of the application of artificial
intelligence in the hospitals.
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Suggesting the effective training styles to the medical staffs so that they can carry out their
responsibilities very well by the use of artificial intelligence systems.
To analyze the outcomes of the application of artificial intelligence systems in the areas in
which, it is already incorporated.
Research hypothesis
Research hypothesis can be understood as the statement that is to be proved or disproved by
investigating the research problem. The research hypothesis is important for be formulated so
that the research can be carried out in an effective manner (Fletcher, 2017). There are mainly two
types of research hypothesis as the Null hypothesis and Alternate Hypothesis. The null
hypothesis is denoted by H0, and the alternate hypothesis is denoted by H1.
H0: There is no significant benefit of incorporation of artificial intelligence in the healthcare
sector.
H1: There are major advantages of the application of artificial intelligence in the healthcare
system.
Research methodology
Research methodology can be defined as the systematic and structured way of conducting
research. A researcher can make use of two major types of research methodologies to conduct
the study and arrive at the desired conclusions. The two types of research methodologies are
Qualitative and Quantitative research. Quantitative research is the research in which the
attributes that cannot be measured in terms of numbers are incorporated in the research. The
quantitative research is the type of research in which the data and information that can be
calculated and recorded in numbers is considered. To carry out this study and have the effective
results, both quantitative and qualitative research methodologies are used by the researcher. The
data in the qualitative research is collected by means of survey and other primary sources of data
whereas the quantitative data is collected by the means of secondary sources like reports,
journals and articles.
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References
Fletcher, A.J., 2017. Applying critical realism in qualitative research: methodology meets
method. International Journal of Social Research Methodology, 20(2), pp.181-194.
Ghahramani, Z., 2015. Probabilistic machine learning and artificial
intelligence. Nature, 521(7553), p.452.
Gunning, D., 2017. Explainable artificial intelligence (xai). Defense Advanced Research
Projects Agency (DARPA), nd Web, 2.
Hassabis, D., Kumaran, D., Summerfield, C. and Botvinick, M., 2017. Neuroscience-inspired
artificial intelligence. Neuron, 95(2), pp.245-258.
Jiang, F., Jiang, Y., Zhi, H., Dong, Y., Li, H., Ma, S., Wang, Y., Dong, Q., Shen, H. and
Wang, Y., 2017. Artificial intelligence in healthcare: past, present and future. Stroke and
vascular neurology, 2(4), pp.230-243.
Moravčík, M., Schmid, M., Burch, N., Lisý, V., Morrill, D., Bard, N., Davis, T., Waugh, K.,
Johanson, M. and Bowling, M., 2017. Deepstack: Expert-level artificial intelligence in heads-
up no-limit poker. Science, 356(6337), pp.508-513.
Yu, K.H., Beam, A.L. and Kohane, I.S., 2018. Artificial intelligence in healthcare. Nature
biomedical engineering, 2(10), p.719.
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