Main Menu

My Account
Online Free Samples
   Free sample   Artificial intelligence assignment impact of ai on healthcare industry

Artificial Intelligence Assignment: Impact Of AI On Healthcare Industry


Task: It is your responsibility to ensure that your assignment arrives before the submission deadline stated above. See the University policy on late submission of work.

For the KF7028 assignment, you must produce a proposal for a short research project. The proposal is the foundation of the 60-credit project that you will study as part of your postgraduate programme, KF7029 MSc Computer Science & Digital Technologies Project.

This assignment is therefore doubly important:

  • It accounts for 80% of the marks for KF7028
  • It is essential preparation for your research project.

As stated, the KFG7029 research project will account for 60 credits (one-third) of your programme of study. Typically, you will spend 600 hours on this project.

Your KF7028 research proposal will be approximately 2500 – 3000 words and specify the project background, motivation and relevance to your programme of study; its scope, aims and objectives; a plan of the major activities. Your proposal should draw on current and recent research and other appropriate sources of information and cite these sources using a consistent standard referencing system. The proposal will be assessed by your allocated module tutors for the module or by your supervisor and a second marker, feedback will be provided, consisting of suggestions and comments on how to improve the project.

You will be allocated your project supervisor in semester two of your study period. If you start your study in September, you will be allocated a project supervisor in second semester January – May. If you start your study in January, you will be allocated your supervisor in your second semester September – January

This proposal should be based on the outcome of your own research and of the meetings with your tutors, peers and supervisors. This supervisor/tutors will be confirmed with you by the end of week 6. By this time you should have produced a draft copy of your proposal. Your supervisor/tutor will provide individual support and formative feedback during the preparation of your research proposal.

Research question
You should aim to outline a research question. This research question defines what you want to study and is the first step in development of your project proposal.

Produce a summary of what your project will achieve in one or two sentences. 

Background, Motivation and Relevance – literature review

  • Set out and justify, using supporting literature, where your work will fit in the computing body of knowledge.
  • Outline and critically discuss what relevant research has been undertaken, in the past, in your area of interest and why this project is necessary.
  • Outline and critically discuss why the research will be of value, in the future, and what the anticipated impact of the outcomes will be.
  • Provide a diagram such as a mind map illustrating the position in the computing body of knowledge.
  • Outline why you want to undertake this work, some areas to consider are, personal motivation, skills set and career choices, a gap in the knowledge base.

Scope, Objectives and Risk

  • Outline and justify the scope of your project – what you intend to do, you may also want to say what you will not include but might be expected by others to be incorporated.
  • Outline numbered steps (SMART Objectives) you will have to complete in order to achieve the aims and would provide sufficient work to conclude your research question.

After each objective outline the deliverables and or outcomes that will be produced as a result of this objective’s work. Outline how you will assess and or measure the quality for that objective. Outline what research method/design you will adopt for each objective and how each method will support one another.

  • Break down the objectives into tasks and produce a task list, each task should outline, deliverable, resources (all types) required, skills required, time required.
  • Produce a risk log (see example on your Blackboard Assessment tab) for you project. Each objective should be assessed based on risks, such as technical, personal, resources, time, and costs etc factors.

Sources and use of Knowledge

  • Identify and justify a journal where your work would be relevant for publication.
  • Identify and apply aspects of the standards for publication in the target journal that you can incorporate into your project proposal, so for example the referencing system, font style and pitch etc, instructions usually found under the journal’s advice to authors.
  • Identify, justify and critically discuss any authors, journals where previous relevant research has been published within the last 5 years.
  • Ethics, Legal, Social, Security and Professional Issues

Using literature, write out a separate section for Ethics, Legal, Social, Security and Professional Issues. In your deliberations discuss, explore and define all of the issues associated with your project, including how you will consider security issues. If you think an area of this section is not applicable to your project, you should justify why this is the case; leaving any section blank will result in a loss of marks.


The project on artificial intelligence assignment aims to develop the methods to measure the impact of AI (artificial intelligence) in the healthcare industry.

1.1. Research Questions
How to develop methodologies for measuring the impacts of AI for the future on the healthcare industry?

2. Background, Motivation and Relevance – literature review
2.1. Background
Healthcare Industry has got advanced through the use of Artificial Intelligence. Different Applications of Artificial Intelligence have changed the management of the healthcare industry drastically. The applications are namely- Machine Vision, Speech recognition, and Expert system. It allows the healthcare firm to make effective decisions on their (Nandan & Nath, 2020). The decision making processes help leaders of the management to adopt sustainable methods. The use of AI in the decision-making process helps to make proper Human judgment in the workplace (Carr, 2020). Experienced individuals in the healthcare industry can effectively use AI. Artificial Intelligence helps the multinational giants in the healthcare industry to adopt different digital technologies. The Decision-making process through AI in the healthcare Industry helps the healthcare industry to multiply.

2.2. Motivation
Healthcare Industry in recent years has progressed rapidly by the use of AI. The major areas where the use of AI has influenced the healthcare industry are listed below within the artificial intelligence assignment: -

2.2.1. “Clinical Decision Support”-
Implementation of AI in the "Clinical Decision Support" system helps to decrease the errors of the medical policy. "Clinical Decision Support" helps to maintain consistency in the healthcare system (Lu & Burton, 2017). The process of this system entirely depends on the algorithm of machine learning. Such algorithms help the doctors to detect chronic diseases easily. From the year 1970, the “Clinical Decision Support” was in the healthcare industry but traditionally (Reddy, et al., 2019). Traditional methods of “Clinical Decision Support” failed to satisfy the doctors. The conventional approach doesn't have any use, which could help the doctors to detect the disease. AI-based "Clinical Decision Support" helps the doctors to keep a record of the patient’s medical history. The doctors can do the treatment according to the medical history of the patient.

Artificial Neural Networks mentioned in this segment of artificial intelligence assignment are also arising in the market to support the medical diagnosis of the patient. These technological methods help individuals in the healthcare industry to provide proper medical services to the patient.

2.2.2. “Patient Monitoring”-
“Patient Monitoring” is a method of maintaining health records of the patient electronically. The latest electronic devices, such as fitness watches and compatible medical devices are used to record the medical status of the patient (Reddy, et al., 2019). Various applications on smartphones also help to record the pulse rate and blood pressure rate of the patient. Traditionally, there was no such system that can record the medical status of the patient daily. That's why, in earlier days, many wrong diagnoses were made by the doctors (Luxton, 2016). “Patient Monitoring” helps the doctors to access the patient’s health records and treat them accordingly.

The research carried on the case scenario of artificial intelligence assignment illustrates that AI has introduced a new system on "Patient Monitoring," known as "Waveform Pattern Learning." “Waveform Pattern Learning” helps in improving the analysis of different diagnostic methods in health institutions. It helps to diagnose the respiratory disorder among the patients swiftly. “Patient Monitoring” also helps those patients who are suffering from chronic diseases and need long term treatment. Techniques of AI are used for monitoring of the patients. Various Intensive Care Units use software having AI systems for monitoring cardiovascular and respiratory diseases by applying the essential signs. “Doppler ultrasounds”, “electromyographs”, “electrocardiographs”, and, “electroencephalographs” can be analyzed and monitored by “waveform pattern learning” in different hospitals (Rigby, 2019). Electronic devices have to be used to track the health records such as smartphones and devices that can be used for monitoring purposes. This way the data and information regarding the patients can be obtained digitally.

2.2.3. “Healthcare Administration”-
Use of AI in healthcare Administration illustrated herein artificial intelligence assignment makes the system affordable and user-friendly to all the individuals. AI-based tools give integrity to the system. Linking of machine learning techniques with electronic health records help the clinical administrators in the system (Wehbe, et al., 2018). Health Services have also get improved with the use of AI. The patient monitoring system has helped the doctors in a significant way. The individuals of healthcare institutions can now serve the patients effectively (Reddy, et al., 2019). AI-based techniques have also reduced the time of formalities done during the leave of the patient. AI-based algorithms also serve the self-diagnosis system to less critically ill patients. It helps the clinicians to get free time, which they can utilize in other works. 

The paperwork done to record all the data of patients have reduced. Now all the data are recorded electronically. Recording data electronically helps both the patients and healthcare individuals. It can be accessed at any time by both the patients and the healthcare individuals. There are many types of Artificial Intelligence used for the diagnosis and treatment of the patients especially in the administrative activities. It is evident in the context of artificial intelligence assignment that one of the most common forms of AI is machine learning. “Neutral network” is one of the most essential forms of machine learning. It is a technology used since 1960. Another form of machine learning is “deep learning” that is a network model used in “healthcare administration”.

2.2.4. “Healthcare Interventions”-
“Healthcare Interventions” examined in this segment of artificial intelligence assignment have helped to make notable developments in the healthcare industry. Inbuilt machine learning programs in electronic health records help the healthcare institutions to form an integrated way of "Healthcare Intervention." It involves the health monitoring of both the individuals and the groups of individuals. "Healthcare Interventions" consist of AI-based programs which help to make the system digitally integrated (Panch, et al., 2018). Applications are linked with servers of healthcare institutions, which help to analyze the patient record (Reddy, et al., 2019). It helps the doctor to treat the patients efficiently who needs emergency attention. It also reduces the queries raised by the doctors to the patients.

Computer Vision is a technique of "Healthcare Intervention," which is used to analyze the 3D medical imaging process automatically. "Healthcare Interventions" also involves robotic assistants who help the patients to be observed continuously (Yu, et al., 2018). Especially elderly patients get little support from the family. For them, the robotic assistants work like a companion who gives help and care to the patients.

2.3. Literature Review
In Artificial intelligence, the learning of literature is done by two methods. They are listed below within the artificial intelligence assignment:

2.3.1. What are the unsupervised methods discussed in the context of artificial intelligence assignment?
In this learning, no human interaction is needed to control the computer. The computer can derive its purposes automatically. The text-mining algorithm process is used to detect the patterns and the statistical techniques of the (Jiang, et al., 2017). Unsupervised method of learning is mainly used when the working is done on significant data sources. In the sector of healthcare, unsupervised learning is needed because it can handle big data efficiently. The records of a particular patient or a specific department need to be stored in an integrated way. Unsupervised methods of learning will help the management to record these data safely.

2.3.2. Supervised methods
In this learning of artificial intelligence assignment, human interaction is needed to control the computer. Human interaction is needed to teach models to the computer (Jiang, et al., 2017). Supervised learning involves deep learning, along with strong guidance from the researcher. The supervised method of learning is a highly repetitive process. This learning method involves accomplishing several tasks by the computer "on its own."

2.4. Sources and use of knowledge
2.4.1. Journal
Various Journals have been used that are relevant to the topic explored in the sections of artificial intelligence assignment. IEEE Transactions have published several journals on the subject of the impact of Artificial Intelligence on the Healthcare Industry. Most of the researchers consider IEEE citations on Artificial Intelligence as a relevant journal. Also, IEEE transactions contain many publications on the impact of Artificial Intelligence in the Healthcare Industry. The journal taken in this artificial intelligence assignment is recent and related to the topic.

Journals Title

Article Title



Impact Factor





Prof. Swaraj Kumar Nandan, Prof. Mausumi Das Nath



“Artificial intelligence-enabled healthcare delivery”

“Incorporating AI in healthcare delivery”

Sandeep Reddy, John Fox, Maulik P Purohit



“Artificial intelligence in healthcare: past, present, and future. Stroke and vascular neurology,”

“Supervised and Unsupervised Learning”

Jiang f.



Table 1: Author and Journal table

2.4.2. Mind Map


Figure 1: Mind Map (created by author)

3. Scope, Objective, and Risk
3.1. Scope
The scope of the project outlined herein artificial intelligence assignment is to study the effect of Artificial Intelligence on the Healthcare Industry. The applications of AI in the healthcare Industry have risen highly in the past decade. AI also involves machine learning algorithms. It will help future researchers to study machine learning algorithms. A prospective study developed within the artificial intelligence assignment will help to increase the implementation of machine learning algorithms in the Healthcare Industry.

3.2. Objective
The project on artificial intelligence assignment is consisting of the purposes listed below: -

  • Specific: To analyze the effect of AI in the Healthcare Industry.
  • Measurable: To measure the importance of AI-based tools on the Healthcare Industry.
  • Achievable: To study the growth of the Healthcare Industry by using AI-based Devices.
  • Realistic: To determine the impacts of AI in the future on the healthcare Industry.
  • Time-Bound: To study the research in two and a half months.

3.2.1. Research Method Table


Achieving the objectives

To analyze the effect of AI in the Healthcare Industry

The objective can be achieved by evaluating the effect of AI in all sectors of Healthcare.

To measure the importance of AI-based tools on the Healthcare Industry

The objective can be achieved by the studying the demand of AI-based tools in Healthcare Industry.

To study the growth of the Healthcare Industry by using AI-based Devices

The objective mentioned in the artificial intelligence assignment can be achieved by analyzing the development of Healthcare Industry through AI-based tools.

To determine the impacts of AI in the future on the healthcare Industry

The objective can be achieved by studying the impact of AI in the healthcare Industry on future.

To study the research in two and a half months

The objective can be achieved by fulfilling the task within time.

Table 2: research method

3.3. Risk
Many risks have been faced by the researcher while performing the analysis in the context of artificial intelligence assignment. Some of the risk events are listed as follows:

Sl. No.

Risk Event

Risk Likelihood

Impact of Risk

Risk Value

Risk Owner

Mitigating Action


Data Implementation Process is not well defined 





The risk can be reduced by implementing proper data mining processes.


The impact of AI on employee performance is not defined





The risk can be reduced by researching the impact of AI on employee performance.


The project schedule is not planned correctly





The risk can be reduced by scheduling the timing of the project.

Table 3: risk Log

4. Ethics, Legal, Social, Security and Professional Issues of artificial intelligence assignment
4.1. Ethics
The ethics of the project depends on the two rules of ethics. They are: -

4.1.1. Explicit Rules-
The project on artificial intelligence assignment has not violated any of the rules and regulations (Wang & Siau, 2018). The data sets of the project have been gathered from the previous journals (Matsuzaki, 2018). The data set is ethical and has followed all the rules and regulations (Gampfer, et al., 2018). The information collected from previous journals has ethically helped the research.

4.1.2. Implicit Rules-
The project has followed all the norms relating to objectivity, honesty, and respectfulness (Chan & Zary, 2019). The data set of plans for this artificial intelligence assignment has been obtained from ethical sources and has all the standards.

4.2. Legal
In terms of legal issues, the project will not carry any such matters as it affects society positively. The data set is fully gathered from the relevant works of literature, and it has no similarity with vulnerable groups. The project has been strictly conducted on the specific industry (Krausová, 2017). The data set is explicitly taken based on the healthcare Industry. Additionally, as per the law, no physical test has been done on any of the participants (KONSTANTINIDIS, et al., 2019).

4.3. Social
The project will not affect any social groups in society. The project is wholly based on the medical industry and the impact of Artificial Intelligence on it (Nadarzynski, et al., 2019). The plan does not include any individuals for the research purpose. Also, it doesn't affect anyone's emotions while doing the research.

4.4. Security
The project research on artificial intelligence assignment will not harm anyone's security socially. The data set taken for the study has already been published in the public domain (Ghafur, et al., 2019). Thus, no security issues will be raised on the project.

4.5. Professional
In terms of professional issues discussed in the artificial intelligence assignment, the project will not carry such matters because the project will not directly work on the individuals (Gillan, et al., 2019). The topic has been researched to study the impact of AI on the Healthcare Industry (Meskó, et al., 2018). The problem is not directly related to any of the patients or individuals for research.

5. Schedule of Activities
5.1. Work Breakdown Structure


Figure 2: Work Break down Structure

5.2. Tasks List

Task No.

Task name


Start Date

End Date


Literature Review

12 days

(two weeks)

1st of the first month

15th of the first month


Carry out the secondary research method by using journals


1st of the first month

5th of the first month


Study on the different applications of Artificial Intelligence


6th of the first month

10th of the first month


Criticize the literature Review


11th of the first month

15th of the first month


Studying the areas where artificial Intelligence has felt a significant effect

12 days

(two weeks)

16th of the first month

26th of the first month


Choosing the specific areas

4 days

16th of the first month

18th of the first month


Analyzing the researches

4 days

20th of the first month

22nd of the first month


Studying the effects


23rd of the first month

26th of the first month


Extraction of features

6 days

(one week)

27th of the first month

2nd of the second month


Draft writing of research

42 days

(seven weeks)

3rd of the second month

17th of the third month


Choosing the research questions and aim

6 days

3rd of the second month

9th of the second month


Writing a literature review

6 days

10th of the second month

17th of the second month


Analyzing the scope and objectives of the project

6 days

18th of the second month

24th of the second month


Evaluating the risk

6 days

25th of the second month

1st of the third month


Making the various Issues

12 days

2nd of the third month

10th of the third month


Proofreading and reviewing the proposal

6 days

11th of the third month

17th of the third month


Review and Submitting the Proposal

3 day

(half a week)

17th of the third month

17th of the third month

Table 4: Risk Log

5.3. Gantt Chart


Table 5: Gantt Chart

5.4. Monitoring and Control Table

Sl. No.




Do the risks are reviewed periodically?

Reviewing the risk regularly by the owner.


Does the risk are analyzed regularly?

The risk should be identified and analyzed regularly by the owner.


Does the risk are communicated with the stakeholders?

The risk must be communicated with the stakeholders.

Table 6: monitoring and controlling

6. References
Carr, S., 2020. ‘AI gone mental’: engagement and ethics in data-driven technology for mental health. s.l.:Taylor & Francis.

Chan, K. S. & Zary, N., 2019. Applications and challenges of implementing artificial intelligence in medical education: integrative review. Artificial intelligence assignment JMIR medical education, 5(1), p. e13930.

Gampfer, F., Jürgens, A., Müller, M. & Buchkremer, R., 2018. Past, current and future trends in enterprise architecture—A view beyond the horizon. Computers in Industry, Volume 100, pp. 70-84.

Ghafur, S., Grass, E., Jennings, N. A. & Darzi, A., 2019. The challenges of cybersecurity in health care: the UK National Health Service as a case study. The Lancet Digital Health, 1(1), pp. e10-e12.

Gillan, C. et al., 2019. Professional implications of introducing artificial intelligence in healthcare: an evaluation using radiation medicine as a testing ground. Journal of Radiotherapy in Practice, 18(1), pp. 5-9.

Jiang, F. et al., 2017. Artificial intelligence in healthcare: past, present and future. Stroke and vascular neurology, 2(4), pp. 230-243.

KONSTANTINIDIS, S. et al., 2019. Artificial intelligence for participatory health: applications, impact and future implications.

Krausová, A., 2017. Intersections between law and artificial intelligence. International Journal of Computer, 27(1), pp. 55-68.

Lu, S. & Burton, S. L., 2017. Man vs Robots? Future Challenges and Opportunities within Artificial Intelligence (AI) Health Care Education Model. Artificial intelligence assignment Proceedings of the RAIS Conferece I, Volume 6, p. 7.

Luxton, D. D., 2016. An introduction to artificial intelligence in behavioral and mental health care. In: Artificial intelligence in behavioral and mental health care. s.l.:Elsevier, pp. 1-26.

Matsuzaki, T., 2018. Ethical Issues of Artificial Intelligence in Medicine. Cal. WL Rev., Volume 55, p. 255.

Meskó, B., Hetényi, G. & Gy?rffy, Z., 2018. Will artificial intelligence solve the human resource crisis in healthcare?. BMC health services research, 18(1), p. 545.

Nadarzynski, T., Miles, O., Cowie, A. & Ridge, D., 2019. Acceptability of artificial intelligence (AI)-led chatbot services in healthcare: A mixed-methods study. Digital health, Volume 5, p. 2055207619871808.

Nandan, S. K. & Nath, M. D., 2020. Impact Of Artificial Intelligence In Making Better Marketing Decisions In Healthcare Industries. Our Heritage, 68(8), pp. 53-59.

Panch, T., Szolovits, P. & Atun, R., 2018. Artificial intelligence, machine learning and health systems. Journal of global health, 8(2).

Reddy, S., Fox, J. & Purohit, M. P., 2019. Artificial intelligence-enabled healthcare delivery. Journal of the Royal Society of Medicine, 112(1), pp. 22-28.

Rigby, M. J., 2019. Ethical dimensions of using artificial intelligence in health care. Artificial intelligence assignment AMA Journal of Ethics, 21(2), pp. 121-124.

Wang, W. & Siau, K., 2018. Ethical and moral issues with AI: a case study on healthcare robots. s.l., s.n., p. 2019.

Wehbe, Y., Al Zaabi, M. & Svetinovic, D., 2018. Blockchain ai framework for healthcare records management: Constrained goal model. s.l., IEEE, pp. 420-425.

Yu, K.-H., Beam, A. L. & Kohane, I. S., 2018. Artificial intelligence in healthcare. Nature biomedical engineering, 2(10), pp. 719-731.


Related Samples

Question Bank

Looking for Your Assignment?

Search Assignment
Plagiarism free Assignment









9/1 Pacific Highway, North Sydney, NSW, 2060
1 Vista Montana, San Jose, CA, 95134