LITERATURE REVIEW OF ARTIFICIAL INTELLIGENCE IN MEDICAL SECTOR

 literature review of Artificial Intelligence in Medical Sector

            Several research studies are conducted on the topic of artificial intelligence and its adaptation in the healthcare centers for the improvement of the service. Hengstler and Ellen Enkel summarized their research findings by elaborating that automations having the in-built qualities of learning and working according to artificial intelligence is rapidly enhancing with their application. MEDICAL ASSISTANCE DEVICES AND AUTONOMOUS CARS ARE FINE EXAMPLES OF THIS CLAIM. EVEN SUCH DEVICES ARE COMMONLY ADOPTED IN SOCIETY IN VARIOUS AREAS OF LIFE BUT STILL, THERE is SKEPTICISM. IN ACCORDANCE WITH THE CONCEPTS RELATED TO THE HUMAN SOCIAL INTERRELATIONS TRUST IS THE BASIS FOR THE RELATIONSHIP BETWEEN THE AUTOMATION AND HUMAN BEING. SOMEHOW, RESEARCH ALSO PROVIDE INFORMATION ABOUT THE METHODS USED BY THE ORGANIZATIONS TO ENCOURAGE THE CONCEPT OF TRUST RELATED TO ARTIFICIAL INTELLIGENCE (BEING USED IN THEIR ADMINISTRATIVE SYSTEMS).  research studies concluded dichotomous constitution of trust about the applied systems of Artificial Intelligence (AI).        

        A research study on the Artificial Intelligence (AI) held in 2001, summarized that principal constituents of computational intelligence are basically, neural networks, evolutionary algorithms, and uncertain logic that has focus on the mutual enhancement. Research paper also presented findings as such formalisms has direct link with the application AI in the health care centers. In the medical fields and health care centers the fuzzy logic support in working with imprecise information (Hengstler & Ellen Enkel, 2016). WHILE NEURAL NETWORK HAS the CAPABILITY TO LEARN BEHAVIOR OF THE SYSTEMS THROUGH THE USE REPRESENTATIVE EXAMPLES. WHILE EVOLUTIONARY ALGORITHMS INCLUDES THE ABILITY to optimize THE COMPLEX SYSTEMS WHEN MATHEMATICAL MODELS ARE NOT THERE FOR ASSISTANCE. NEURAL SYSTEM HAS GREAT IMPORTANCE IN THE MEDICAL FIELD BECAUSE OF THE ABILITY OF IMAGE PROCESSING. A MULTIPLE VALUED THRESHOLD LOGIC SYSTEM KNOWN AS THE CELLULAR NEURAL NETWORK WILL BE USED FOR THE PURPOSE OF DOCUMENTING THE MEDICAL IMAGES.

            Another research study conducted in 2013 provide findings that Artificial Intelligence (AI) a continuously developing technology that is making progress more rapidly in comparison to other technologies. in accordance to the research study conducted by setiawan, p.a.venkatachalam, & m.hani in 2009 artificial intelligence help out the MACHINE TO WORK ACCORDING TO THE HUMAN BEING THROUGH UTILIZING THE installed and stored data in the memory (Aizenberga, Aizenberga, Hiltner, Moraga, & Bexten, 2001). However, IT IS NOT POSSIBLE TO INSTALL OR STORE ALL DATA IN THE MEMORY OF the machine just on the basis of assuming the possible future experience the machine or a computer will face. However when it goes outside the circle or do not meet the stored data or information machine can not perform the desired actions. That can be considered as the BIGGEST LIMITATION OF artificial intelligence. Research elaborate that Artificial Intelligence (AI) is just similar to human intelligence as machines having Artificial Intelligence (AI) ARE PROGRAMMED IN SUCH A WAY TO UNDERSTAND AND ACT ACCORDING TO THE HUMAN BEING (Setiawan, P.A.Venkatachalam, & M.Hani, 2009). In the research studies tactile sensor e-skins (having relatively same qualities of Human skin) is introduced as the component of the Artificial Intelligence (AI) that is going to be investigated more.  In the modern world a number of different types of e-skins are created through the use of technology that has incredible abilities of sensing. Other than this modern robots as interactive robots are working with the Artificial intelligence that has excellent qualities of sensing and understanding the objects in subjective and objective ways. Such robots can work in the healthcare centers to facilitate the medical staff by taking care of the elderly and nursing patients through the use of artificial intelligence (AI (Jones, 2015)).   

References of ARTIFICIAL INTELLIGENCE IN MEDICAL SECTOR

Agah, Arvin. 2013. Medical Applications of Artificial Intelligence. CRC Press. Accessed 11 13, 2018.

Aizenberga, Aizenberga, J. Hiltner, C. Moraga, and E. Meyer zu Bexten. 2001. "Cellular neural networks and computational intelligence in medical image processing." Image and Vision Computing 177–183.

Boden, Margaret A. 1996. Artificial Intelligence. Elsevier. Accessed 11 13, 2018.

Fieschi, M. 2013. Artificial Intelligence in Medicine: Expert Systems. Springer. Accessed 11 13, 2018.

Harris, Michael C. 2010. Artificial Intelligence. Marshall Cavendish. Accessed 11 13, 2018.

Hengstler, Monika, and Selina Duelli Ellen Enkel. 2016. "Applied artificial intelligence and trust—The case of autonomous vehicles and medical assistance devices." Technological Forecasting & Social Change 105: 105-120.

IntroBooks. 2018. Artificial Intelligence. IntroBooks. Accessed 11 13, 2018.

Jiang, Fei, Yong Jiang, Hui Zhi, Yi Dong, Hao Li, Sufeng Ma, Yilong Wang, Qiang Dong, Haipeng Shen, and Yongjun Wang. 2017. "Artificial intelligence in healthcare: past, present and future." Stroke and vascular neurology 2 (4): 230-243. Accessed 11 13, 2018.

Jones, M. Tim. 2015. Artificial Intelligence: A Systems Approach: A Systems Approach. Jones & Bartlett Learning. Accessed 11 13, 2018.

Koh, Hian Chye, and Gerald Tan. 2011. "Data Mining Applications in Healthcare." Journal of Healthcare Information Management 19 (2): 65. Accessed 11 13, 2018.

Poole, David L., and Alan K. Mackworth. 2017. Artificial Intelligence. Cambridge University Press. Accessed 11 13, 2018.

Setiawan, Noor Akhmad, P.A.Venkatachalam, and Ahmad Fadzil M.Hani. 2009. "Diagnosis of Coronary Artery Disease Using Artificial Intelligence Based Decision Support System." Proceedings of the International Conference on Man-Machine Systems. Accessed 11 13, 2018.