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Assessment 3: Individual Case Study
Due Date: Week 12 Friday 11:45 PM AEST
Weighting: 40%
Assessment Task:
This is an individual assessment.
Each of you will analyse a given case study and identify the issues arising from the case study. Based on the issues found in the case study, you will identify three e-business use cases (for example, Predictive Maintenance). You will then choose as many emerging technologies as appropriate to address those use cases. You can choose any emerging technologies that fit the use cases, even the ones not covered in the lectures.
You will write a report illustrating how the chosen emerging technologies would fit into and address the requirements of the identified e-business use cases.
In the main body of the report, you will include the following topics.
1. A background study of the chosen emerging technologies
- You need to describe how the chosen emerging technologies evolved, their underlying designs, working principles, functions, and capabilities.
2. A brief description of the future potentials of the chosen emerging technologies
- You need to discuss the future applications of the chosen emerging technologies in e-business in general.
3. An illustration of how the chosen emerging technologies would fit into the identified e-business use cases
- You need to illustrate what issues of the identified use cases would be resolved by the chosen emerging technologies.
4. Details of how the chosen emerging technologies would address the requirements of the identified use cases
- You need to elaborate how the chosen emerging technologies would interoperate to fulfill the requirements of the identified use cases.
Please note: Discussions for topics 1-2 should be generic, while discussions for topics 3-4 must be in the context of the Assessment 3 Case Study. The Introduction section of the report should clearly state the identified e-business use cases and the emerging technologies chosen to address those use cases.
The length of the report should be 3000 words. Your report must have a Cover Page (Unit Id, Assessment number/name, Student names, Student Ids, Campus, and Tutor name) and a Table of Contents (this should be MS word generated). A standard report structure, including an executive summary, must be adhered to. You are required to review more than 10 articles (including at least 4 academic references) relevant to the chosen use cases and emerging technologies.
Bottom of Form
Caution: ALL assessment submissions will be checked for similarity by Turnitin. If are found to be involved in plagiarism, contract cheating or any other kind of academic misconduct, you may face penalties from zero marks for the assignment to fail grade in the unit, or even exclusion from the university. Please make yourself familiar with the University’s Student Academic Integrity Policy and Procedure which is available in the policy portal https://www.cqu.edu.au/policy.
Assessment Submission:
Each of you must upload the written report to Moodle as a Microsoft Word file by the above due date. It is the responsibility of the students to submit the correct final versions of their assessment items.
Assessment Criteria:
You will be assessed based on your ability to demonstrate understanding of the emerging digital technologies, critically evaluate their future impacts, and use those technologies to solve current and forthcoming e-business problems.
The marking criteria for this assessment are as follows.
Executive summary – 3 marks
Table of contents – 2 marks
Introduction – 3 marks
Background information about the chosen emerging technologies – 6 marks
Future potentials and applications of the chosen emerging technologies – 6 marks
How the chosen emerging technologies would fit into the identified use cases – 4 marks
How the chosen emerging technologies would address the requirements of the identified use cases – 10 marks
Conclusion – 3 marks
References – 3 marks
The marking rubric for this assessment is given in the following page.
| Criteria | Quality | ||||
| High Distinction (85-100%) | Distinction (75-84%) | Credit (65 -74%) | Pass (50-64%) | Fail (<50%) | |
| Executive summary | 2.55–3 | 2.25–2.52 | 1.95–2.22 | 1.5–1.92 | <1.5 |
| Covered background information and all findings clearly. | Covered background information and most findings clearly. | Covered background information most findings without clarity. | Covered background information and some findings clearly. | Missed most findings and not clear. | |
| Table of contents | 1.7–2 | 1.5–1.68 | 1.3–1.48 | 1–1.28 | <1 |
| Used decimal notation. Included all headings and page numbers. Used ToC auto-generation. | One feature missing. | Two features missing. | Three or more features missing. | ToC is missing. | |
| Introduction | 2.55–3 | 2.25–2.52 | 1.95–2.22 | 1.5–1.92 | <1.5 |
| Set the scene for the report and described the purpose very clearly. | Set the scene for the report and described the purpose clearly. | Covered most parts with clarity. | Covered some parts with clarity. | Most parts are missing and not clear. | |
| Background information about the chosen emerging technologies | 5.1–6 | 4.5–5.04 | 3.9–4.44 | 3–3.84 | ❤ |
| Covered all parts with detailed explanations. | Covered all parts with detailed explanations. But there is some room for improvement. | Covered most parts with detailed explanations. | Covered some parts with detailed explanations. | Failed to cover most parts and not clear. | |
| Future potentials of the chosen emerging technologies | 5.1–6 | 4.5–5.04 | 3.9-4.44 | 3-3.84 | ❤ |
| Covered all major applications with very clear explanations. | Covered all major applications with clear explanations. But there is some room for improvement. | Covered most of the major applications with clear explanations. | Covered some major applications with clear explanations. | Failed to cover most of the major applications and not clear. | |
| How the chosen emerging technologies would fit into the identified use cases | 3.4–4 | 3–3.36 | 2.6 – 2.96 | 2–2.56 | <2 |
| Provided very good justifications for all chosen technologies with clarity. | Provided good justifications for most of the chosen technologies with clarity. | Provided justifications for most of the chosen technologies with clarity. | Provided justifications for some of the chosen technologies with clarity. | Failed to provide justifications for most of the chosen technologies and no clarity. | |
| How the chosen emerging technologies would address the requirements of the identified use cases | 8.5–10 | 7.5–8.4 | 6.5–7.4 | 5–6.4 | <5 |
| Provided convincing explanations for all chosen technologies. | Provided convincing explanations for most of the chosen technologies. | Provided explanations for most of the chosen technologies but some of them are not convincing. | Provided convincing explanations for some of the chosen technologies. | Failed to provide explanations for most of the chosen technologies and not convincing. | |
| Conclusion | 2.55–3 | 2.25–2.52 | 1.95–2.22 | 1.5–1.92 | <1.5 |
| Stated the summary of the report and concluding remarks with clarity | Stated the summary of the report and concluding remarks, but there is some room for improvement. | Stated the summary of the report and concluding remarks but did not include enough details. | Stated the summary of the report without clarity and concluding remarks are missing. | Both summary of the report and concluding remarks are missing. | |
| References | 2.55–3 | 2.25–2.52 | 1.95–2.22 | 1.5–1.92 | <1.5 |
| All references are listed and cited according to Harvard referencing style. More than 10 very good references were used with at least four very good quality academic resources. | All references are listed and cited according to Harvard referencing style. More than 10 references were used with at least four good quality academic resources. | More than 10 references were used with at least four academic resources. There are minor referencing errors. | Not all references are listed or cited but there are no referencing errors. | No reference list or citation or too many referencing errors. Less than four academic resources are used. |
Answer========================
COIT20250: Emerging Technologies in e-Business
Assessment 2
Artificial Intelligence and Robotics in Health Sector
Submitted By: Submitted TO:
Executive Summary
The main aim of the report is to find the application of the emerging technologies that help to provide better health services to all individuals in the South Western Sydney Local Health District (SWSLHD). This report solves the different issues that made SWSLHD lag behind the technology, rely all on human effort for the betterment of services so it eradicates this problem using different techniques as stated in the report. The report states what AI and robotics might contribute in large amounts in the health sector and what it has contributed so far to improve the clinical strategy of SWSLHD.
This report has findings that have drastically improved the accuracy and precision of health care in AI and robotics. It includes current technologies like booking arrangement and wellbeing following for patients, manifestation checking and employing and preparing the employers for making an impact to the physicians and patients in different ways that helps them outrun the traditional equipment’s however these technologies can have negative impacts through these impacts can be reduced and minimize the risk while undergoing any medical tasks.
Table of Content
2.0 Functions of AI and Robotics. 4
2.1.1 Transporting the Medical Supplies. 4
2.1.2 Sanitation and Disinfection. 4
2.1.3 Control the Coronavirus Disease. 5
2.1.4 Prescription Dispensing Systems. 5
2.1.5 Telepresence Physicians. 5
2.2.2 AI and Wearables for Early Detection. 6
2.3.2 Mechanical technology. 6
2.3.4 Decision Support Clinically. 6
2.3.5 Data Management (both doctor and patient) 7
3.0 Current and Future Applications. 7
3.1 Artificial Intelligence and Consumer Apps for Keeping Well 7
3.1.1 Advancements in AI & Robotics. 7
3.1.2 Versatile training arrangements. 8
3.1.3 Customized medication. 8
3.1.4 Medication disclosure. 8
4.0 Issues of Using AI Robotics in health Sector. 8
4.1 An absence of individual contribution. 8
4.2 An ascent in joblessness rates among medical services labourers. 9
4.3 Probability of a Defective Diagnosis. 9
5.2 Manifestation checking. 10
1.0 Introduction
Artifical Intelligence (AI) robots in medical care refers to the utilization of complex calculations intended to play out specific assignments in a mechanized manner. At the point when analysts, specialists and researchers infuse information into PCs, the recently fabricated calculations can survey, decipher and even propose answers for complex clinical issues (Arsene, 2020). SWSLHD being one of the local health districts in Sydney has a vision to provide best health care facilities for health community as well to improve the current situation of all public hospitals in South Western Sydney. The districts operate 6 hospitals and 14 major community health centres providing Aboriginal health services, Drug health services, Mental health services, early intervention, palliative care and rehabilitation services. SWSLHD has adopted new services and emerging technologies to provide new innovative and responsive care. Their strategies align with one of their six strategic directions which is A healthcare system for the future.
AI and robotics have increasingly become a part of our eco-system and are being adopted in equal measure in the healthcare space. Ai and robotics are one of the moving aspects of the clinical business today. With rising technological aspects, the business will undergo a gigantic change. Equipped with navigation capabilities, these robots can transport documents, medicines and linen to different parts of the hospital. Hospital staff can then focus on more important tasks such as patient care (Banks, 2018). Evolution in AI has Solidified an AI upgraded future prevents tedious work solely by humans having to remember each and every aspect of data.
2.0 Functions of AI and Robotics
Robots are one of the primary brought into the world robotized machines, create to perform different activities helping people to finish different every day or tedious assignments in a limited capacity to focus time. Furthermore, presently utilizing AI, advanced mechanics designers are building AI robots that can all the more likely comprehend the different situations and work all the more productively (Bisen, 2020). AI and Robotics have different functions in different health aspects
2.1.1 Transporting the Medical Supplies
Clinical supplies and other basic things utilized in medical clinics, or clinical focuses can be presently provided by these prepared robots. As a matter of fact, robots can be created with self-route innovation, to move in the emergency clinic premises to arrive at a patient’s room or different spots without human assistance. AI robots are prepared with a tremendous measure of AI preparing information with sensor combination area innovation to make the navigational abilities of transportation robots more powerful.
2.1.2 Sanitation and Disinfection
To evade human contacts, and limit the transmission of exceptionally infectious illness like COVID-19 and different contaminations, robots are the most ideal choices to use for purifying or cleaning the tainted zones. It can just, splash the synthetics and purify the enormous zones with rapid sparing time and endeavours.
2.1.3 Control the Coronavirus Disease
Computer based intelligence robots are utilized for purification and sterilization can be cleaned, as it is likewise presented to debased regions, and become tainted. While people presented to such ailing zones, it makes him wiped out or unexpected problems. In this way, robots can be utilized for sterilization or purification at various areas.
2.1.4 Prescription Dispensing Systems
AI robots can perform precisely at better speed, which is a significant viewpoint for the medical care industry to give exact subtleties or prescription and work quicker for the fast reaction and ideal therapy to patients. Essentially, a computerized administering framework with cutting edge highlights, are created to point where robots would deal with powder, fluids and profoundly gooey materials with better speed and exactness. Such robots can administer numerous different things when introduced at clinics or clinical focuses.
2.1.5 Telepresence Physicians
Telepresence doctors – a sort of augmented reality doctor is additionally used to look at and treat patients from far off areas or rustic regions. Robots with Telepresence can furnish the sentiment of getting talked with a genuine specialist, making the two-way correspondence conceivable among them.
2.1.6 Surgical Assistants
AI empowered robots can be created to help specialists to perform different assignments. Such robots are furnished with including more improved common sound system representation, joined with expanded reality. What’s more, these robots are prepared with various sorts of preparing information through PC vision to cause them to comprehend the situation and play out the correct activity likewise (Bisen, 2020).
2.2 Utilities
A clinical AI and robotics framework’s engineer could list the total arrangement of utilities (e.g., progressing admittance to clients’ de-recognized datasets, whereupon the AI and robotics framework’s turn of events and approval are based, in addition to the client’s creation framework and its information whereupon the AI’s runtime activity depends) that may influence a particular hub’s activity, and evaluate and deal with every one of them ( Matheny, M., Israni, S.T., Ahmed, M. and Whicher, D., 2020).
2.2.1 Robotics in Treatment
- Kaspar is a child-sized humanoid robot to support autistic children
- Giraff is a mobile communication robot that facilitates chronically ill patients with outside world
- Bestic robot-assisted dining appliance for people who are unable to move their hands or arms
- Toyota has created four robots that enable immobilized patients to walk or balance
- Xenex robots disinfect hospital facilities
- Aethon’s TUG robots automate the delivery and transportation of the immense amount of materials in hospitals, thus freeing staff to focus on patients
- Veebot is a robot that can draw blood faster and more safely than a human.
2.2.2 AI and Wearables for Early Detection
- Circadia- iTBra -Wearable vest for detection of breast cancer
- CardioDiagnostics – Remotely monitor heart irregularities
- Innovaccer’s AI Assisted Care Coordination Platform addresses persistent issues in care and connectivity
- Sentrian is a remote patient intelligence service provider
- Royal Philips delivers remote care options to proactively help patients at home
- Google DeepMind is partnering with University College London Hospital’s radiotherapy department
- IBM’s Watson for Oncology gives treatment recommendations based on patient’s medical records.
2.3 Capabilities
The obstacles fuel contrasts in capacities between huge, refined elements—that is, wellbeing frameworks, wellbeing back up plans, or huge innovation organizations—and littler engineers that may do not have the assets to create AI robots in a privacy protective style. Notwithstanding, security and development in medical services AI robots are not in exacting resistance. More current mechanical methodologies, for example, differential protection and dynamic assent can help empower advancement while as yet ensuring protection (Matheny, M., Israni, S.T., Ahmed, M. and Whicher, D., 2020)
2.3.1 Advanced mechanics
AI robots in medical services are presently assuming a major function in giving a mechanized answer for medication and different divisions in the business. Artificial intelligence organizations are currently utilizing enormous information and other valuable information from the medical services industry to prepare robots for various purposes (Bisen, 2020).
2.3.2 Mechanical technology
Artificial intelligence in mechanical technology making such machines become more savvy, from the information and perform different essential assignments without the assistance of people. Thus, you have to think about such robots, how they are utilized in clinical fields and what are the sorts of advanced mechanics utilized in the medical services industry (Bisen, 2020).
2.3.4 Decision Support Clinically
AI Robotics in medical services can demonstrate valuable inside clinical choice help to assist specialists with settling on better choices quicker with design acknowledgment of unexpected problems that are enlisted definitely more precisely than by the human cerebrum. The time spared and the conditions analysed are indispensable in an industry where the time taken and choices made can be life changing for patients (Arsene, 2020).
2.3.5 Data Management (both doctor and patient)
AI Robotics in medical care is an extraordinary expansion to the data the board for both doctor and patient. With patients getting to specialists quicker, or not in any way when telemedicine is utilized, important time and cash are spared, removing the strain from medical care experts and expanding solace of patients (Arsene, 2020). Specialists can likewise advance their learning and increment their capacities inside the activity through AI-driven instructive modules, further demonstrating the data the board abilities of AI in medical services.
https://pagead2.googlesyndication.com/pagead/js/adsbygoogle.js?client=ca-pub-44627600714543013.0 Current and Future Applications
AI is already being used to detect many deadly diseases, such as cancer, more accurately and in their earlier and more treatable stages. Nursing homes in China have started using robots called Robear to provide care for the elderly to lift and move patients in and out of bed into a wheelchair, help those who need assistance to stand, and even turn patients in bed to prevent bedsores. In Australia, there is an increasing number of aged care facilities that have started using robots to perform duties such as transporting linen, medical supplies and meals. This efficient delegation of tasks enables staff to focus more on providing quality care to patients. In addition, AI and other digital technologies such as wearables, connected devices, and telemedicine can help drive greater patient engagement.”
Robots come in as an aid for these workers so that they can do their job better, or workers can be re-skilled to be able to perform jobs that provide more value-add.” Robots are only going to work hands-in-hands with the healthcare professionals in the coming future. It is unlikely in the near future for surgeons to be replaced. These robots can only help the surgeon perform specific tasks faster in offering improved precision, better imaging and navigation. The surgeon is still needed to perform the surgery.”
3.1 Artificial Intelligence and Consumer Apps for Keeping Well
- Smart Belt- Welt – Alerts the person when they overheat.
- Smart Performance Apparel – Offers real time biometrics, personalised programming to help athletes reach their goals faster.
- Samsung Electronics – Offers consumers devices such as smart watches and activity trackers.
- Lumo Lift – Posture monitoring device.
- Under Armour -Will use IBM Watson to provide customised advice for sleep, fitness and activity.
- Pathway Genomics – Provide customised health advice
3.1.1 Advancements in AI & Robotics
- Japanese government has entered into a public-private alliance with government affiliated National Institutes of Biomedical Innovation, Health and Nutrition to develop a self-learning AI
- BERG Health initiated a phase II clinical trial in 2016 for a drug compound to treat pancreatic cancer
- Atom wise found two existing drugs to work against Ebola virus, with the help of AI technology
- IBM has announced 3 new consumer- focussed partnerships, one of which is Under Armour
- KroniKare is developing a mobile application that assesses chronic wounds and presents a preliminary assessment to nurses or other healthcare workers.
- Woodlands Health Campus (WHC), Singapore is exploring the use of technology to improve the patient care experience.
- The National University of Singapore (NUS) is studying the mechanisms of nature to develop new medical technology that will fulfil a range of unmet clinical needs in the healthcare industry.
- University of Sydney announced the launch of Sydney Imaging, a next-generation medical imaging facility’s core research facility that is dedicated to research and training.
3.1.2 Versatile training arrangements
Versatile training arrangements come through prompting patients and improving treatment results utilizing constant information assortment. There’s an enormous push in telemedicine as of late too with organizations utilizing AI for minor conclusion inside cell phone applications.
3.1.3 Customized medication
The capacity to investigate a lot of patient information to distinguish treatment choices. The innovation can recognize treatment choices through cloud-based frameworks ready to deal with normal language.
3.1.4 Medication disclosure
Medication disclosure is another extraordinary spot for AI to slip in with pharma organizations ready to incorporate bleeding edge innovation into the costly and protracted cycle of medication revelation. The advantages of AI are immediately clear with the attention on efficient and design acknowledgment after testing and ID of new medications.
In beginning phase drug disclosure, new companies, for example, Benevolent AI or Verge Genomics are known to receive calculations which search through bits of information for designs excessively complex for people to distinguish, sparing both time and developing such that we in any case might not have had the option to.
4.0 Issues of Using AI Robotics in health Sector
SWSLHD can have certain issues by using AI and Robotics in health sector
4.1 An absence of individual contribution
Medical procedure robots are totally coherent and are not modified to feel any compassion towards the patients. A few specialists see it as a hindrance. In actuality, human capacities regarding individual contact with the wiped out go past those of PCs. Associations between a specialist and a patient are critical in building trust and treatment. AI instruments can work with minor mistakes that won’t influence the diagnosing cycle or activity extensively. In contrast to PCs, doctors can abuse a few guidelines to do their most extreme to spare an individual’s life.
4.2 An ascent in joblessness rates among medical services labourers
Since AI has been executed all through the entire arrangement of medical services on a more terrific scope, numerous exercises that were generally performed by people should be possible by machines these days. Chatbots and robots can give psychological well-being help, break down the state of patient’s wellbeing, and predict a few issues like seizures, sepsis, heart failure, and so forth. Thusly, numerous individuals can lose their work.
This point is still talked about, despite the fact that AI is probably not going to supplant specialists in the closest future. Nonetheless, the AI programming is uncovered to identify diseases from the X-beams with higher exactness than radiologists can.
4.3 Probability of a Defective Diagnosis
The precise analysis for a specific ailment relies upon different information gathered from a large number of individuals who have encountered comparative side effects and conditions. To get the fitting examination, the AI information base ought to contain adequate data about the patients of the specific gathering. In this manner, if there is an absence of data about an individual from a specific foundation, AI can give a wrong determination. Accordingly, the specialists are probably going to give an inappropriate treatment in the event that they are not experienced enough to recognize the mix-up. Mistakes brought about by ineffectively prepared AI instruments account nearly for 200,000 patient passing’s every year and the US wellbeing framework’s yearly loss of about $20 bn.
4.4 Social Prejudices
AI-based machines can’t completely comprehend human instinct and the foundation that makes them one-sided against the patients being analysed. For example, the AI calculation can suggest an individual with low salary a nursing office that is unreasonably expensive for them. The significant expense of administrations at such offices debilitates the patient to proceed with the treatment. The specialist, can choose the best reasonable treatment plan considering the patient’s social and budgetary status (AI adoption in Healthcare: 10 Pros and Cons | ByteAnt, 2020).
5.0 Use Case
SWSLHD can apply these strategies to help improve the status of the local district people;
5.1 Booking arrangements
The possibility of a chatbot connected to a booking application is the same old thing. Yet, with regards to medical care, such bots would permit clients to plan regular check-ups without any problem. For instance, a chatbot called Iris can timetable and drop arrangements, get lab results, and send subsequent updates. A chatbot planned explicitly for the requirements of a clinical focus could permit patients to book their arrangements in under a moment while never connecting with a human operator or secretary. On account of such an execution, patients can just choose their PCP, pick the planned time allotment, embed their own data, and even include data about their manifestations with the goal that the specialist is advised on the purpose behind the visit. The bot would then be able to send subsequent messages by means of text, email, or even voice message to remind patients about the booked arrangements. The best bit of leeway of chatbots here is that they can manage numerous client requests simultaneously, and the staff won’t be overpowered with the quantity of requests, regardless of how high it gets (Krzysztof, 2020).
5.2 Manifestation checking
Medical services suppliers are currently actualizing bots that permit clients to check their indications and comprehend their ailment from the solace of their homes. Chatbots that utilization Natural Language Processing can comprehend quiet demands paying little mind to the info variety. This is basic for meeting the high precision of reactions, which is basic in manifestation checkers. With the information on the information, the bot can survey data and assist clients with narrowing down the reason behind their manifestations. With all the information gave by the bot, clients can decide if proficient treatment is required or over-the-counter prescriptions are sufficient.
Perhaps the best case of such chatbots is Ada, which was made by researchers, designers, and specialists. Improved with NLP and AI abilities, Ada can assist patients with deciding likely sicknesses and propose potential therapies without any problem.
This is a success win circumstance for patients and specialists. Patients can set aside their time and cash while treating minor sicknesses with over-the-counter prescription, and specialists possess energy for patients who require more consideration (Krzysztof, 2020).
5.3 Wellbeing following
Patients who need clinical help consistently can profit by chatbots too. For instance, suppliers can utilize bots to make a connection between their primary care physicians and patients. Such a bot can give a point by point record of the followed ailments and help evaluate the impacts of endorsed the executives drug.
A case of such a chatbot is Florence, an individual clinical framework intended for individuals who go through long haul clinical consideration. Clients of the bot can get additional data about facility areas and advantage from highlights, for example, wellbeing following, drug update, and measurements (Krzysztof, 2020).
5.4 Employing and preparing
Huge medical care organizations are continually recruiting and onboarding new workers. To deal with these applications, they typically wind up producing a great deal of desk work that should be rounded out and certifications that should be twofold checked. By associating chatbots to such offices, the activity of Human Resources divisions will get simpler. For instance, new workers could buy in to a chatbot and get incorporated into the onboarding cycle for a recently recruited employee or get data about the organization. An association can utilize chatbots to send records to recently recruited employees at whatever point required, naturally remind fresh recruits to finish their structures, and robotize numerous different undertakings, for example, demands for excursion time, maternity leave, and others (Krzysztof, 2020)
6.0 Conclusion
Thus, this report contains findings of (SWSLHD) can improve AI and robotics in wellbeing and can present encountering a solid increasing speed with the expansive augmentation of utilizations in the above fields as mentioned to improve the health status of people in its area. Algorithmic medication has just become a reality and will turn out to be progressively significant in the years to come. Notwithstanding the likely advantages of AI in the field of wellbeing, there are various components which ought to be considered and which ought to be incorporated on the grounds that these developments to be set up in the public eye. This measures definitely will have a positive impact in the current situation and to other health district as well.
References
Aluaş, M., Maniac, V. and Vaida, M., 2019. Using Artificial Intelligence in health: call for legal regulation. Applied Medical Informatics, 41, pp.23-23.
Arsene, C., 2020. Artificial Intelligence In Healthcare: The Future Is Amazing – Healthcare Weekly.
Banks, J., 2018. The human touch: practical and ethical implications of putting AI and robotics to work for patients. IEEE pulse, 9(3), pp.15-18.
Bisen, V., 2020. How AI Robotics Is Used In Healthcare: Types Of Medical Robotics. [online] VSINGHBISEN.
Buhler, K., 2020. 3 Ways Artificial Intelligence Will Change Healthcare. [online] Forbes.
Byteant.com. 2020. AI Adoption In Healthcare: 10 Pros And Cons
nforma.com.au. 2020. The Development Of Robotics And AI In The Health Sector – Informa Australia.
Krzysztof, M., 2020. Chatbots In Healthcare: Benefits, Risks, And Use Cases | Code Blog. [online] Codete Blog – We share knowledge for IT Professionals.
Matheny, M., Israni, S.T., Ahmed, M. and Whicher, D., 2020. Artificial intelligence in health care: The hope, the hype, the promise, the peril. Natl Acad Med, pp.94-97.
Priyanka Bajpai, 2018. Cover Story: Robotics and AI – Face of New Health. BioSpectrum Asia, pp.BioSpectrum Asia, June 14, 2018.
Robots.net. 2020. Robotics In Healthcare: How Robots Benefit The Medical Industry? | Robots.Net. [online]
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