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Artificial Intelligence Assignment: Implementing AI in healthcare Industry

’ of Design Thinking Process to get a better understanding of the problem in hand and the solution that can be introduced in order to tackle it (Luxton, 2015). The framework of the model has been presented in the below diagram. The various elements that have been captured in the report are as follows: ‘What is’ – During this phase, the analysis of the scenario is undertaken. ‘What if’ – The brainstorming activity takes place in order to visualize a new and modern scenario. ‘What wows’ – It involves refining and evaluating the undertaken decisions. ‘What works’ – It is the ultimate phase of the design thinking process where the implementation and execution take place. Source: (Peer Insight | Innovation Consulting, 2018) What is…? The “What is” is the foundation of the design thinking process that is designed to get a better understanding of the existing reality. In order to understand the present scope of AI in the healthcare setting, secondary sources of data were used including research publications and peer-reviewed articles. The primary source of data was also used and a total of 4 healthcare professionals were interviewed about the AI techniques that are used in their care facility. The semi-structured interview questions were presented before them so that their views on the AI implementation in the healthcare sector could be ascertained. One of the possible uses of the Artificial Intelligence Robotic concept in the healthcare setting includes the robotic surgery and the screening of the neurological conditions. This innovative concept has a tremendous scope and its optimum implementation could bring about a revolutionary change in the care setting and the care services that are offered to the patients (Fan et al., 2018). In spite of the high utility of AI robots in the healthcare setting, this concept has been growing at a slow pace and there is high scope to expand the application of AI robots in the healthcare setting (Rich & Knight, 2009, p 3). The target users of the artificial intelligence assignment include the healthcare service providers and facilities that offer care services to the patients and other care users. The target users would also include the clinics where physicians work independently. Empathy Map: The empathy map presented below shows the views of a healthcare physician named Dr Jones. His views have been presented in the map and it shows that there is scope to introduce AI robots in the healthcare facilities so that the work burden of the physicians and doctors can be managed in a better and more efficient way. Source: (Nielsen Norman Group, 2018) Stakeholder Map: The various stakeholders that are involved in case of Dr Jones have been presented in the below image. This map was created to identify the various individuals with whom the physician engages on a regular basis while working in the healthcare facility. Journey Map: The journey map highlights a day in the life of Dr Jones. I was created to understand how he manages his functions in the healthcare setting. The hectic schedule naturally takes a toll on the service quality that is offered by him. From this journey map, it was identified that there is scope to introduce an AI robotic model that can help physicians like Jones to share their work burden. What if…? This stage fundamentally transforms the insight of the target audience into the suitable problem and opportunity statement so that the suitable solutions can be arrived at. The objective is to introduce an innovative technology-based model in form of an AI robot that can minimize the burden of doctors and physicians. Since the use of AI can impact both the doctors and the care users, the concept of AI robotics in the healthcare context has been explored here. The primary and secondary research in this artificial intelligence assignment indicated that the four elements that could be enhanced by introducing the AI model in the healthcare setting include the Mental and physical wellbeing of doctors The improvement in the health conditions of care users The ‘how we might’ approach was implemented in order to capture the issues and design the suitable opportunity in the healthcare sector. Problem How Might we question Opportunity Adverse implication on the wellbeing of physicians How might technology be introduced to minimize burden in healthcare setting? Introduction of AI robotic models Introducing automation Poor health outcome of patients How can health and wellbeing of care users be enhanced by incorporating AI in the setting? Focusing on personalized approach while treating the patients. Synchronizing the work of AI robots and human factors. Mental and physical wellbeing of doctors – A number of questions were framed in order to understand the mental and physical make-up of the doctors. Their wellbeing is extremely important to make sure that they deliver quality services to the users. The high extent of manual processes naturally makes them saturated and increases their work burden. It ultimately impacts their work quality (Piette et al., 2016). In order to empower them, the AI robots or technological innovative models can be introduced to positively influence the services of these professionals. The improvement in the health conditions of care users – The health outcome of the patients is directly linked to the service that is delivered by the doctors. In order to influence it in a positive manner, there is the scope to expand the application of technology so that the doctors can get assistance while serving the care users. What Wows On the basis of the arrived problem and opportunity, it can be stated that technological elements can be introduced in the healthcare setting in order to simplify the care services and enhance the health outcome of the patients. In order to create value for the involved stakeholders, the solutions have been designed by focusing on the short-term concept and the medium to long-term concept (Xing, Krupinski & Cai, 2018). The napkin pitch framework has been used to understand how the proposed solution would meet the needs of the target users. Short-term solution concept Need Healthcare professionals are under pressure to meet the healthcare needs of the patients. It takes a toll on their capability as professionals and impacts the health outcome of the patients. Approach Gradual introduction of AI concept to do the diagnosis of patients and treating them for minor medical conditions Benefit Reduction in the work burden of healthcare professionals like nurses and assistants. Other service providers Policies can be introduced to familiarize the care professionals with the innovative concept. Improved experience of Dr Jones Need Reduction in pressure of Dr Jones Approach Simplification of work model. Benefit Improved healthcare service for the patients Other service providers Streamlined work in healthcare setting Medium to Long-term solution concept Need High awareness of care users about improved healthcare service Value proposition for the involved stakeholders Approach A higher degree of involvement of innovation and patients in the process. Benefit Better health outcome of patients. Other service providers Uniformity and consistency in treatment model. Improved experience of Dr Jones Need Jones’ Higher awareness of the needs of the care users Value proposition for the involved stakeholders Approach Better involvement of Jones, patients and the innovative approach. Benefit Synchronized behaviour by Jones and other stakeholders Other service providers Better understanding of the medical system. Assumption Testing Concept Testing Assumption Make or Break Data needed for testing Short-term solution concept Desirability Flexible schedule for the healthcare professionals ? Secondary research to understand Feasibility Simple synchronization of work between AI robots and doctors ? How AI can be modelled to create Validity Use of existing IT resources ? Value for care users and doctors Long-term solution concept Desirability Proper understanding of the automated approach by the care users and care providers ? Primary research to get feedback on the AI robotic concept Feasibility Building a robust automated network in the are setting ? in the healthcare setting. Validity Collaborative approach to bring about uniformity in the AI concept. ? What works…? This is the ultimate stage of the design thinking process that involves refining of the solution so that value can be created for the target users. The assumption test The solution concepts that have been introduced would create value for the target audience. The comparison of the short-term and long-term solution shave been presented below based on assumptions (Xing, Krupinski & Cai, 2018). The solutions would be useful but the feasibility, desirability and viability would be different. Conclusion The design thinking process has been implemented in this artificial intelligence assignment to introduce the AI robotic concept in the healthcare so that the service setting could be strengthened. The project intends to create value for the care users and minimize the manual work process of the care providers. Both the primary and the secondary research techniques have been used in order to frame the design that could enhance the AI integration in the delicate work setting. In order to understand the effectiveness of the project in this artificial intelligence assignment, the feedback must be taken from the involved stakeholders to understand how it would create value for them. Artificial intelligence assignment assignments are being prepared by our IT assignment help experts from top universities which let us to provide you a reliable assignment help online service. References Arnold, D. and Wilson, T., 2017. What doctor? Why AI and robotics will define new health. PwC. Fan, W., Liu, J., Zhu, S. and Pardalos, P.M., 2018. Investigating the impacting factors for the healthcare professionals to adopt artificial intelligence-based medical diagnosis support system (AIMDSS). Annals of Operations Research, pp.1-26. 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. Hamet, P. and Tremblay, J., 2017. Artificial intelligence in medicine. Metabolism, 69, pp.S36-S40. Koch, M., 2018. Artificial intelligence is becoming natural. Cell, 173(3), pp.531-533. Luxton, D.D. ed., 2015. Artificial intelligence in behavioral and mental health care. Academic Press. Nielsen Norman Group. (2018). Empathy Mapping: The First Step in Design Thinking. [online] Available at: https://www.nngroup.com/articles/empathy-mapping/ [Accessed 5 Oct. 2018]. Peer Insight | Innovation Consulting. (2018). Three Go-To Resources on Design Thinking. [online] Availableat:http://www.peerinsight.com/musings/2013/10/24/my-go-to-resources-on-design-thinking [Accessed 5 Oct. 2018]. Peer Insight | Innovation Consulting.(2018). Three Go-To Resources on Design Thinking. [online] Availableat:http://www.peerinsight.com/musings/2013/10/24/my-go-to-resources-on-design-thinking [Accessed 5 Oct. 2018]. Rich, E. and Knight, K., 2009. Artificial intelligence Third Edition. McGraw-Hill, New. Rich, E. and Knight, K., 2009. Artificial intelligence Third Edition. McGraw-Hill, New.


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