Artificial Intelligence in Healthcare Applications

This assignment delves into the multifaceted applications of Artificial Intelligence (AI) within the realm of healthcare. It examines how AI is employed for knowledge management in electronic health records (e-health), how it aids in clinical decision-making processes through simulation models, and explores the ethical implications of AI's growing influence in healthcare. The discussion encompasses various perspectives, including trust in AI-powered medical devices, the potential impact on democracy due to big data and AI, and the role of AI in evidence synthesis and interpretation for behavior change.

Running head: ARTIFICIAL INTELLIGENCE IN HEALTHCARE
-Unit Code-
-Unit Name-
-Assessment Number-
PROFESSIONAL SKILLS FOR INFORMATION AND COMMUNICATION
TECHNOLOGY- ARTIFICIAL INTELLIGENCE IN HEALTHCARE
-Due Date-
Name of the Student
-Number of the Student-
-Email Address-
-Campus lecturer/tutor-
- Unit Coordinator-
-Name of the University-

1ARTIFICIAL INTELLIGENCE IN HEALTHCARE
Executive Summary
The purpose of this report is to briefly describe the use of Artificial Intelligence in a
Healthcare organization. A small software organization established in 2015 specializes in AI
production and supplies. Being an ICT manager one has to describe the aspects of providing
products to the healthcare organizations in Sydney metropolitan area. The organization is
foresee the development of their small scale business in next five years in Australia by using
AI in healthcare. The project is to provide a report on the development of the selected
healthcare organization by conducting some preliminary research. The key issue of AI in
healthcare is restricting innovation in the healthcare for protecting patients. This is a huge
challenge for the AI developers to keep the safety of the patients in mind thus need enormous
training and knowledge of both technical and biological perspective. It has been concluded
from the report that ‘power of AI in healthcare is undeniable’. Thus, recommendation has
been done according to the development of AI industry as well as betterment of Healthcare
associations keeping in mind the safety and security of the patients.

2ARTIFICIAL INTELLIGENCE IN HEALTHCARE
Table of Contents
1. Introduction............................................................................................................................3
2. Artificial Intelligence.............................................................................................................4
2.1. Artificial Intelligence in Healthcare................................................................................4
2.2. Revolution of Artificial Intelligence...............................................................................5
2.3. AI Developments in Healthcare Industry........................................................................6
3. Application of Artificial Intelligence.....................................................................................7
3.1. Application Proposal in Australian Medical Association...............................................8
3.2. Potential Advantages and Disadvantages of the proposals.............................................8
3.3. Proposed Strategy Ethical, Social and Legal Considerations.........................................9
4. Conclusion............................................................................................................................10
5. Recommendation..................................................................................................................11
References................................................................................................................................13

3ARTIFICIAL INTELLIGENCE IN HEALTHCARE
1. Introduction
Artificial intelligence defines the usage of the computer system that able the
performance of the tasks that are generally needs Human Intelligence. Human intelligence
includes functionalities like visual perception, speech recognition, decision-making and
languages translation. Artificial intelligence may stimulate the human decision-making
process. AI relies over human training and does not replace human intelligence (Karam
2014). The report is based on the project preparing an investigation on the requirement of the
selected Healthcare organization ‘Australian Medical Association’ on the aspect of
developing its IT infrastructure. Thus, usage of AI increases the feasibility of expansion in
business of this healthcare organization within the next five year. The Secretary General
(CEO) of the software organization thus may conduct preliminary research and present. The
CEO has the responsibility of daily basis management of the organization and report
accordingly. The Australian Medical Association (AMA) represents the most influenced
organizational partnership for the registered medical practitioners as well as medical students
of Australia (Zang et al. 2015). AMA helps the patients by improving the care by supporting
the medical professions by huge options of services. But this services is provided keeping in
mind the AMA Code of Ethics that represents the core of fundamental principles.
The objective of this report is to identify the advances in intelligent computing or AI
impact over healthcare organizations by providing retails, transport, financial services,
operating equipments and many other things. Comparing the technological approaches used
in Artificial Intelligence and thus addressing the issues relating to the development of AI in
Healthcare. To conduct the investigation, primary and secondary approach has been used and
thus how the information has been gathered. The report has been divided into two parts, in
the first part general discussion of Artificial intelligence, revolution and implementation of

4ARTIFICIAL INTELLIGENCE IN HEALTHCARE
AI oriented development has been proposed by some conversational idea for the betterment
of organization. And in the second part critical analysis of the proposed advancement of AI in
the organization is displayed.
2. Artificial Intelligence
Artificial Intelligence as stated by John McCarthy, “The science and engineering of
making intelligent machines, especially intelligent computer programs”, refers the possibility
of turning a software think intelligently equivalent to human thinking (Acampora et al. 2013).
The main aim of Artificial Intelligence (AI) is to create systems that can exhibit similar
human behavior and meet decision-making advancement. The use of algorithms that find
patterns in data without explicit instruction. A system might learn how to associate features
of inputs such as images with outputs such as labels.
2.1. Artificial Intelligence in Healthcare
As in the above discussion it has been clarified that AI “the use of computer systems
able to perform tasks that normally requires human intelligence like visual perception, speech
recognition, decision-making and translation between languages” (Ashrafian, Darzi and
Athanasiou 2015). However, Artificial Intelligence helps in simulation of human decision-
making but relies over training of the human intelligence. Other than structured data,
numbers, facts AI is programmed to understand the natural language as well. Thus, AI
technology is trained to make some logical decisions over time (Wong and Bressler 2016).
Artificial intelligence provides rapid advancement technology in Healthcare and provides a
lot more rich and relevant information to the customers and HCPs with on-demanding
confidence to medical and clinical assessments. Artificial Intelligence has greatly advanced in
the past few years especially in the healthcare professional (HCP) and patient
communications (Jha and Topol 2016). Availability of Artificial Intelligence has grown to an

5ARTIFICIAL INTELLIGENCE IN HEALTHCARE
extent that it not only helps in curing the disease but also supports personality profiles beyond
the diseases.
AI is taking a huge impact in advancing the management of all kind of organization
especially Healthcare organizations. A software company attempts to solve the diverse
healthcare challenge in Australian Medical Association (AMA) for the improvement of
diagnosis outcome engaging the medical research (Ziuziański, Furmankiewicz and Sołtysik-
Piorunkiewicz 2014). The healthcare organization in Australia is emerging toward the
development of the markets. AI is spreading a huge opportunity for optimization care
delivery, outcomes and costs by utilizing cognitive computing.
2.2. Revolution of Artificial Intelligence
In last 5 years, there has been a huge impact of AI in this world. There has been a
quantum leap in the quality and reliability of a wide range of the daily technological aspect.
In healthcare organization there are several complex and vital activities that includes making
of the medical diagnoses, predicting the machines that may fail to reach certain market value
in the Healthcare organizations, includes a lot of data sets and non-linear relationship within
the entities (Dilsizian and Siegel 2014). These complex prediction, feature specification and
data optimization are promised to deliver by the modern Artificial Intelligence. In HCPs there
are requirement of advance in image recognition. There are advanced image recognition that
has been displayed far beyond expectation. There are availability of medical startups that can
utilize X-rays, MRIs, and CT scans. These technologies are more rapidly used and displays
accurate radiologists (Furmankiewicz, Sołtysik-Piorunkiewicz and Ziuziański 2014).
There are several types of AI applications that are beyond quantum-computing
conundrum are generally called the Artificial Intelligence system(Bennett and Hauser 2013).
These are merely known as the advanced machine learning software that has extensive

6ARTIFICIAL INTELLIGENCE IN HEALTHCARE
behavioral algorithms, which can adapt any situation. These machine are improving their
skills and thus are not only getting smarter in the existential sense (Russell 2015). These can
carry large data sets such that to store enough information in large organizations. Some
examples of AI that are used vigorously now-a-day are: Apple Siri, Alexa, Tesla, Pandora,
Cogito, Boxever, Amazon.com and many more (Hengstler, Enkel and Duelli 2016). In
Healthcare organization AI is generally used for the data storage, analyze complex medical
data, diagnosis processes, treatment protocol development, drug development, personalized
medicine and patient monitoring and care, among others and human behavioral algorithm.
Cortana and Siri have enormous power system with AI capabilities (Luxton 2014). There is a
great potential for the applications for providing huge value when combined with healthcare
applications (Vasant 2015). Healthcare applications are used to patient education material,
deliver medication alerts and human-like interactions to understand a patient's current mental
state. In the form of a personal assistant can have an incredible impact on the application of
AI for monitoring and assisting patients with some of the requirements in the unavailability
of clinical personnel (Michie et al. 2017).
Some of the outcomes relating to healthcare in different parts of the world that
manages medical records and other data, participating in repetitive jobs like test, CT scan,
treatment designing, digitalize consultation, Virtual nurses, Medication management and
several other aspects of healthcare organizations (Helbing et al. 2017).
2.3. AI Developments in Healthcare Industry
The applications that are related to the better outcome of any health care industry
represent the most important AI development that are necessarily to be implemented to the
Healthcare Industry. AI capabilities and mobile apps, patients can receive feedback on a
number of data elements captured on their phone or wearable devices. Whether it relates to
medication adherence or is simply a motivational voice that encourages fitness activities and

7ARTIFICIAL INTELLIGENCE IN HEALTHCARE
healthy habits, AI as a personal life coach creates a customized experience for each
individual patient and offers proactive alerts, which could be sent back to physicians.
3. Application of Artificial Intelligence
Most of the organizations has been disrupted by the influx of several new
technologies in the age of information (Kreps and Neuhauser 2013). In the case of
automation, healthcare plays a similar role. In fact the machine learning Artificial Intelligence
(AI) the doctors, hospitals, organizations, insurance companies also ties to impact in a more
positive way. These companies also searches for a substantial way for the betterment of their
associated organizations (Furmankiewicz, Sołtysik-Piorunkiewicz and Ziuziański 2014).
Some of the commonly used applications that helps in the advancement in any health care
organization having IT infrastructure:
 Treatment Design: AI system has been developed and implemented in analyzing the
data, take note and report the details of patients, external researches of the
organization, and many more. Thus, helps in selecting customized treatment for each
individual.
 Virtual Nurses: Digitalized nurses are set up that helps in maintain the regular check
up of the patients with monitoring the conditions and follow up with treatment within
intervals.
There are similar kind of management in healthcare organization like: Managing
Medical, Records and Other Data, Doing Repetitive Jobs, Digital Consultation, Drug
Creation, Medication Management, Health Monitoring, Precision Medicine and
Healthcare System Analysis

8ARTIFICIAL INTELLIGENCE IN HEALTHCARE
In the revolution of this Artificial Intelligence across science and economy, researchers
are unleashing artificial intelligence (AI) more often. This is done in the form of neutral
network over data torrent. In earlier days “deep learning” system had to be done for the
programmers to expertise in the field of AI, no AI does not requires to be programmed with
human expert’s knowledge. AI has growth so advanced within last few years that now they
can learn on their own, and this has been made possible from collection of large training data
sets. The pattern and spot anomalies in data sets could be understood only by AI and is hard
for the human being to understand and cope up.
3.1. Application Proposal in Australian Medical Association
As per the recommendation by CEO to the healthcare organization of Australian
Medical Association, there need three main application requirements: Healthcare System
Analysis, Medication Management and Creation of drugs.
Almost 97% of healthcare invoices are digital. An organization can use AI to check
through the data for pin pointing the mistakes in treatments, inefficiency in workflow and
helps healthcare system areas to avoid unnecessary patient hospitalizations (Bennett and
Hauser 2013). In this way, a sample of the AI solution may offer to the healthcare
organization of Australian Medical Association. The capabilities of automation and digital
workforces the innovation will be pushed from providers solutions to save time, lower costs,
and increase accuracy will be possible (Russell 2015).
The AiCure application can be included in IT infrastructure to monitor the that could
be used for medication by a patient can be utilized by the organization of healthcare in
Australia (Russell 2015). A webcam is paired up with a smart phone having AI infrastructure
to autonomously confirm that patients are taking their prescriptions and helps them manage
their condition. Most common users could be people with serious medical conditions, patients

9ARTIFICIAL INTELLIGENCE IN HEALTHCARE
who may tend to go against the advice of the doctor’s and other participants in clinical trials
(Bennett and Hauser 2013).
And the last one is by Creating drugs that are necessary for the organization.
Developing pharmaceuticals through clinical trials, which can takes more time and cost a lot
more. This may make the process of curing much faster and cheaper since customized
medicines could change the aspect of the Healthcare organizations (Jones 2015).
3.2. Potential Advantages and Disadvantages of the proposals
Some of the potential advantages of the proposal is that Modern health information
systems facilitates the improvements in many ways like Faster diagnoses, Fewer malpractice
claims, Improved care coordination, Prompt treatment & Reduced errors (Luxton 2014). The
combination of benefits facilitates the collaboration within the providers and the patients that
results in effective case managements in the organization and healthcare industry, which in
turn, can reduce the cost and helps to take care of the providers by making some meaningful
use of the massive amounts of data provided.
Despite of the advantages there are several disadvantages as well the availability of
evidence and confirms in improvement of population in health outcomes and equity. Making
much accurate utilization of the services provided. Keeping user satisfaction in mind and
lowering the costs in health systems with a stronger orientation in primary care. The experts
range from lawyers to engineers, who gather to discuss current and emerging legal, social,
and ethical issues from robotics and artificial intelligence. Day one consisted of six panels
that focused on technical and theoretical issues with robots and AI. The five panel
discussions on day two focused on the regulatory challenges, as well as some solutions.

10ARTIFICIAL INTELLIGENCE IN HEALTHCARE
3.3. Proposed Strategy Ethical, Social and Legal Considerations
With more powerful, technology becomes more difficult for it could be used for
useful reasons and betterment for the future. This applies not only to robots produced to
replace human soldiers, or autonomous weapons, but also to AI systems that can cause
damage if used maliciously. Because these fights will not be fought on the battleground only,
cyber security will become even more important. After all, people are dealing with a system
that is faster and more capable than us by orders of magnitude (Bennett and Hauser 2013).
Though artificial intelligence is capable of a speed and capacity of processing that is
far beyond that of humans, it cannot always be trusted to be fair and neutral. (Norris 2017).
Intelligence comes from learning, whether you’re human or machine. Systems usually have a
training phase in which they "learn" to detect the right patterns and act according to their
input. Once a system is fully trained, it can then go into test phase, where it is hit with more
examples and we see how it performs (Acampora et al. 2013). Artificially intelligent helps in
making the human conversation and relationships better. Economic system are based on
contribution to the economic compensation. The majority of companies are still dependent on
hourly wages work when it comes to production and services. However, by using artificial
intelligence, a company can drastically change and thus relying on the human workforce will
make task easier meaning that the revenue will ultimately go to fewer people.
4. Conclusion
The outline of the project has the impact on the development of artificial intelligence
(AI) systems by exploring the impact of Artificial Intelligence in Health care organization. As
the selected organization is Australian Medical Association. Where there is a requirement a
change in the IT infrastructure and include some AI equipments for the betterment of patients
and development of the organization. Artificial intelligence has been designed and studied

11ARTIFICIAL INTELLIGENCE IN HEALTHCARE
about computer program that reacts to a wide variety of situations very flexibly and
intelligently. It has a growing influence over modern computers related technologies and
thus assures most of the complicated tasks possible. The development of new hardware and
techniques is fueling ongoing movements to build Artificial Intelligence that can understand
and thinks in a cognitive way. However, the potential advantages of such systems are yet
unknown to all, and equally unknown are the potential technological developing the
intelligent machinery. Exploring the basic impact of the AI system on society and proposing
a plan keeping in mind the enhancement of ethical and professional role for the artificial
intelligence developers. Spreading an emphasis over the interpersonal communication of the
organization with its patients, employee and customers and thus spreading the impact
awareness amongst all. There are many useful aspect of Artificial intelligence in most of the
domains, and are still willing for constant growth in the IT oriented industries. The initial step
is to program the automated reasoning in Artificial intelligence. Thus, doing this the
Automated reasoning can compute and take some of the encoded knowledge as input and
hence provide proper conclusion on the basis of knowledge as their output.
5. Recommendation
There are four simple steps to implementing Artificial Intelligence in clinical
organizations: Remote patient monitoring, Connectivity, Training AI and Comprehensive
business model
Recommendation 1: The improvement of AI must be inclined towards more specific
approach other than generic. Implementing AI in remote patient monitoring (RPM) systems
is the first step. When medical-grade wearable devices can provide real-time, clinically
accurate data they have the potential to improve health outcomes through coaching and
feedback.

12ARTIFICIAL INTELLIGENCE IN HEALTHCARE
Recommendation 2: The control over the applications of AI in the Healthcare organization
must be robust and technically supportive. The two main considerations in maintaining
constant connectivity are security and data offloading. Security concerns can be offset by
instituting Virtual Private Networks (VPNs) and external networks. Data collection and
aggregation are AI’s greatest needs, but requires constant, secure connectivity
Recommendation 3: The usage of AI in the industry must have properly trained staffs to
control the AI according to the requirements. AI could help improve health outcomes through
its ability to expediently aggregate, cross-reference, and learn from data to determine its
correlation to patient objectives. To improve health outcomes, AI’s advanced machine
learning algorithms require significant training periods to analyze large datasets specific to
chronic medical conditions.

13ARTIFICIAL INTELLIGENCE IN HEALTHCARE
References
Karam, A., 2014. Artificial Intelligence in Health Care.
Zang, Y., Zhang, F., Di, C.A. and Zhu, D., 2015. Advances of flexible pressure sensors
toward artificial intelligence and health care applications. Materials Horizons, 2(2), pp.140-
156.
Acampora, G., Cook, D.J., Rashidi, P. and Vasilakos, A.V., 2013. A survey on ambient
intelligence in healthcare. Proceedings of the IEEE, 101(12), pp.2470-2494.
Ashrafian, H., Darzi, A. and Athanasiou, T., 2015. A novel modification of the Turing test for
artificial intelligence and robotics in healthcare. The International Journal of Medical
Robotics and Computer Assisted Surgery, 11(1), pp.38-43.
Wong, T.Y. and Bressler, N.M., 2016. Artificial intelligence with deep learning technology
looks into diabetic retinopathy screening. JAMA, 316(22), pp.2366-2367.
Jha, S. and Topol, E.J., 2016. Adapting to artificial intelligence: radiologists and pathologists
as information specialists. JAMA, 316(22), pp.2353-2354.
Ziuziański, P., Furmankiewicz, M. and Sołtysik-Piorunkiewicz, A., 2014. E-health artificial
intelligence system implementation: case study of knowledge management dashboard of
epidemiological data in Poland. International Journal of Biology and Biomedical
Engineering, 8, pp.164-171.
Dilsizian, S.E. and Siegel, E.L., 2014. Artificial intelligence in medicine and cardiac imaging:
harnessing big data and advanced computing to provide personalized medical diagnosis and
treatment. Current cardiology reports, 16(1), p.441.

14ARTIFICIAL INTELLIGENCE IN HEALTHCARE
Furmankiewicz, M., Sołtysik-Piorunkiewicz, A. and Ziuziański, P., 2014. Artificial
intelligence systems for knowledge management in e-health: the study of intelligent software
agents. Latest Trends on Systems, 2, pp.551-556.
Bennett, C.C. and Hauser, K., 2013. Artificial intelligence framework for simulating clinical
decision-making: A Markov decision process approach. Artificial intelligence in
medicine, 57(1), pp.9-19.
Russell, S., 2015. Ethics of artificial intelligence. Nature, 521(7553), pp.415-416.
Luxton, D.D., 2014. Artificial intelligence in psychological practice: Current and future
applications and implications. Professional Psychology: Research and Practice, 45(5), p.332.
Hengstler, M., Enkel, E. and Duelli, S., 2016. Applied artificial intelligence and trust—The
case of autonomous vehicles and medical assistance devices. Technological Forecasting and
Social Change, 105, pp.105-120.
Vasant, P., 2015. Handbook of Research on Artificial Intelligence Techniques and
Algorithms, 2 Volumes. Information Science Reference-Imprint of: IGI Publishing.
Michie, S., Thomas, J., Johnston, M., Mac Aonghusa, P., Shawe-Taylor, J., Kelly, M.P.,
Deleris, L.A., Finnerty, A.N., Marques, M.M., Norris, E. and O’Mara-Eves, A., 2017. The
Human Behaviour-Change Project: harnessing the power of artificial intelligence and
machine learning for evidence synthesis and interpretation. Implementation Science, 12(1),
p.121.
Helbing, D., Frey, B.S., Gigerenzer, G., Hafen, E., Hagner, M., Hofstetter, Y., van den
Hoven, J., Zicari, R.V. and Zwitter, A., 2017. Will Democracy Survive Big Data and
Artificial Intelligence. Scientific American. Feb, 25.

15ARTIFICIAL INTELLIGENCE IN HEALTHCARE
Furmankiewicz, M., Sołtysik-Piorunkiewicz, A. and Ziuziański, P., 2014. Artificial
Intelligence and Multi-agent software for e-health Knowledge Management
System. Informatyka Ekonomiczna, 2, p.32.
Kreps, G.L. and Neuhauser, L., 2013. Artificial intelligence and immediacy: designing health
communication to personally engage consumers and providers. Patient education and
counseling, 92(2), pp.205-210.
Oliveira, T., Novais, P. and Neves, J., 2014. Development and implementation of clinical
guidelines: An artificial intelligence perspective. Artificial intelligence review, 42(4), pp.999-
1027.
Jones, M.T., 2015. Artificial Intelligence: A Systems Approach: A Systems Approach. Jones
& Bartlett Learning.
Bennett, C.C. and Hauser, K., 2013. Artificial intelligence framework for simulating clinical
decision-making: A Markov decision process approach. Artificial intelligence in
medicine, 57(1), pp.9-19.
Norris, D.J., 2017. Introduction to Artificial Intelligence. In Beginning Artificial Intelligence
with the Raspberry Pi (pp. 1-15). Apress.