Robotics and Artificial Intelligence in Healthcare Assignment Sample

• Subject Name : Nursing

Perspectives of Robot-Aided Interventions in Clinical Practice

Introduction to Robotics and Artificial Intelligence in Healthcare

In today’s world, the use of technology is a widely accepted idea. Although the general population is not entirely aware of the reach of technological benefits or even drawbacks, the advancements in science continue for the betterment of humanity. There is a widespread debate on the use of artificial intelligence as well as robotics in the matter of healthcare, as the field is an amalgamation of human compassion and care along with the required use of science and technology. As Maddox et al., 2019, rightly point out the increasing interest of the use of Artificial intelligence in healthcare and attribute it as being revolutionary to the healthcare system. It is spoken as a means to enhance the quality, precision and speed of care provided to patients. The use of artificial intelligence is known as the mimicry, perfection and enhancement of human intelligence by computer systems. Thus, the dialogue remains open on the calculated use of it in a healthcare system that requires a constant touch of human compassion in the speedy recovery of a population. The use of artificial intelligence could possible change the world’s preparation and response to increasing epidemics and pandemics. It could be used to identify infections patterns around the world as well as the spread of it within a timeframe. This hold the power to accumulate, assess and predict data for the future and help in the timely build of prevention measures.

Understanding Robotics and Artificial Intelligence in Healthcare

According to Jiang et al., 2017, Artificial intelligence in healthcare will be a drastic change to the system. One that can catapult the gain and availability of various forms of data for healthcare uses. It will make use of rapid analytical techniques and enhance progress. It can also be used in several types of healthcare data that includes data that is structured as well as non-structured. The wide reach of artificial intelligence tools can be seen in addressing some of the major disease areas like cancer, neurology as well as cardiology. It plays a major role in the various stages of a health care provision. This includes the use of it in the early detection and diagnosis stage as well as the treatment and outcome prediction process. It is also used in the prognosis evaluation and recovery follow up stages. A paper by Alotaibi, 2020, mentions some of the ground breaking AI systems like IBM Watson Health, CloudMedX Health and others that have played a major role in the integration of AI within the healthcare field.

Another important aspect of the use of artificial intelligence in healthcare is the adoption and impact it has on a society. According to Vellido, A, 2019, this data-cantered practise of AI comes with its own challenges to society. As the process of AI integration continues to be commodified at a fast pace, it also demands that societal issues and adjustments not be ignored in order for smooth development of it within the field. The discussion revolves around the suggestion that norms be formed based on a human-centred approach that takes into consideration the society’s perspectives, requirements as well as its constraints. Societal issues include fairness, privacy as well as anonymity, explainability and the ability to interpret. It also demands addressing the role of ethics and legislation in the use of AI in healthcare.

The article by Barbour et al., 2019, examined the future of Artificial Intelligence (AI) in healthcare. Sometimes it is misjudged with regard to the healthcare professionals as a harm in humanism enshrined in medicine’s Hippocratic oath. At a summit these doubts were addressed where they studied AI. AI reframed as machines assisting humans not machines replacing humans, implementation of medical AI is largely uncharted and formal education on AI is paramount. All of the members of the summit indicated positive understanding of AI on health care and its future with a still belief of less humanistic healthcare after the survey. The only mlimitation was the fact that the non-medical practitioners were not included in the summit to acknowledge the impact of AI on them.

In another paper by Beran et al., 2013, the author scouted a psychological response of the parent to the technological distraction. It was a vaccination process and it a medium of pain management, definitely outweighing the pain stimulus. The humanoid robotic distraction came in a s a source of entertainment and mad ethe children forget about the pain associated with the procedure. It even put the parents at mor ease. Compared to the kids who were vaccinated in control conditions it was noticed that children around the AI cried less too. Maybe it was the mystique around unseen technology but it quickly found popularity in paediatric patientcare and more requests poured as parents also wanted the AI. The techno psychological effect was an excellent way to identify, explore and coach through general anxiety around painful but unavoidable medical procedures. The author concluded that positive alteration in the field of technology that could aid healthcare, especially in the field of paediatrics would be needed immensely in the future.

In a paper by Tarassenko et al., 2017, the central goal of infusing technology into medical practice was the idea that one day they might replace doctors. The clicnical evolution saw major upheaval in 2017, even more than the evolution of the past 60 years combined. Which goes to show that better understanding and comprehensive learning could even develop AI to a self-sufficient extent. Making the AI meaningful is the next big step which can enhance the quality of health care provided in the age of digital medical revolution. The objective is to outperform human medical performers and have an insightful clinical impact.

Recent studies have shown robot-based systems actively participated in training and therapizing and rehabilitation process (Ona et al 2019). The idea is to figure out how the robot-based system can be made more flexible for their incorporation in daily life. The understanding that their adaptability to the dynamics of clinical evolution is still limited comprehending how they can be useful in a regular context. A through and gradual improvement on the technological front is the obvious answer along with mechanical overhaul on existing techniques for addressing reliable and effectual schemes for neurorehabilitation and future advancement on motor regains on everyday activities

When referring the contrived connotation of technical assistance provided by Robot based system researchers have found that despite the overall positive image technology still lags behind when compared to real time assistance. Various empirical studies showed how the assistive nature was an evident reason to doubt the complete dependability in crucial health situation.it cannot be denied that AI has actually added low cost, quicker healthcare helping both patient and medical worker yet the adaptability aspect is still up for debate. However, radiology and dentistry have benefited immensely from the features of AI, setting an example for precise foundation in health care.

With regard to assimilating it in more complex scenarios with complete independence will require more work on the technological front. Its superior data collection technology along with precision make sit an extremely lucrative and helpful tool at the precipice of this medical revolution yet upper extremity motor function is not something that can be vouched for so easily.

Evaluation of Robotics and Artificial Intelligence in Healthcare

One of the most important aspect of this discourse has to be the account of the patient perspective in accepting AI powered health care. Though individuals interacting in the medical care workspace will admit that the advantages outweigh the limitation of AI powered healthcare, there is still a minor percentage of the patient population that feels the replacement of human intelligence will not be a good idea for the patients. Some were even worried about the misuse of data and technological shortcomings.so much of it depends on the patient’s perspectives and their view about this type of healthcare. Despite real world effectiveness in numerous arenas related to health care the future of AI int this field relies not just on its persevered technological evolution but also the engagement uptake and adherence of these interventions by patients worldwide.

References for Robotics and Artificial Intelligence in Healthcare

Maddox, T. M., Rumsfeld, J. S., & Payne, P. R. (2019). Questions for artificial intelligence in health care. Jama, 321(1), 31-32.

Jiang, F., Jiang, Y., Zhi, H., Dong, Y., Li, H., Ma, S., ... & Wang, Y. (2017). Artificial intelligence in healthcare: past, present and future. Stroke and vascular neurology, 2(4), 230-243.

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

Davenport, T., & Kalakota, R. (2019). The potential for artificial intelligence in healthcare. Future healthcare journal, 6(2), 94

Emanuel, E. J., & Wachter, R. M. (2019). Artificial intelligence in health care: will the value match the hype?. Jama, 321(23), 2281-2282.

Alotaibi, S. R. (2020). Applications of Artificial Intelligence and Big Data Analytics in m-Health: A Healthcare System Perspective. Journal of Healthcare Engineering, 2020.

Vellido, A. (2019). Societal issues concerning the application of artificial intelligence in medicine. Kidney Diseases, 5(1), 11-17.

Barbour, A., Frush, J., Gatta, L., McManigle, W., Keah, N., Bejarano-Pineda, L., & Guerrero, E. (2019). Artificial Intelligence in Health Care: Insights From an Educational Forum. Journal Of Medical Education And Curricular Development, 6. doi: 10.1177/2382120519889348

Beran, T., Ramirez-Serrano, A., Vanderkooi, O., & Kuhn, S. (2013). Humanoid robotics in health care: An exploration of children’s and parents’ emotional reactions. Journal Of Health Psychology, 20(7), 984-989. doi: 10.1177/1359105313504794

Tarassenko, L., & Watkinson, P. (2017). Artificial intelligence in health care: within touching distance. The Lancet, 390(10114), 2739. doi: 10.1016/s0140-6736(17)31540-4

Oña, E., Garcia-Haro, J., Jardón, A., & Balaguer, C. (2019). Robotics in Health Care: Perspectives of Robot-Aided Interventions in Clinical Practice for Rehabilitation of Upper Limbs. Applied Sciences, 9(13), 2586. doi: 10.3390/app9132586

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