AI Health Check Monitoring and Managing Content Up and Data in CMS World

Authors

  • Harish Paruchuri Anthem, Inc.

DOI:

https://doi.org/10.18034/mjmbr.v5i2.554

Keywords:

Artificial Intelligence, Health Check Monitoring, CMS, Human Intelligence

Abstract

The advent of artificial intelligence (AI) as a means for improved health care bids extraordinary prospects to advance clinical lineup results and patient, reduce costs, and influence populace health. A1 health check monitoring jobs can take care of executing certain basic and advice rules of cleaning up repositories of data which are not getting used to managing the assets which are referred for a long time deleted that big companies with huge contents and assets struggle in keeping the server up and running 24/7. Thus, the objective of this article is to understand the “why to” and the “how-to” of employing all the major health systems in the CMS world. Also review artificial intelligence when compared to human intelligence in the health sector, Data bias, diversity in artificial intelligence teams, and impacts of artificial intelligence on the patient-provider relationship. To give this subject matter, we deployed literature approaches to examine major content that will help in achieving the purpose of this study. The review shows the need for a combination of artificial intelligence and human intelligence produces an augmented intelligence that focuses on creating a more assisting and supportive role for the algorithm. Also, it portrays trust, equity and inclusion need to be prioritized in the healthcare artificial intelligence development and deployment processes, and data management.

 

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Author Biography

  • Harish Paruchuri, Anthem, Inc.

    Senior AI Engineer, Department of Information Technology, Anthem, Inc., USA

References

Abraham, C., and Sheeran, P. (2007). The Health Belief Model. In Cambridge Handbook of Psychology, Health and Medicine, edited by S. Ayers, A. Baum, C. McManus, S. Newman, K. Wallston, J. Weinman, and R. West, 2nd ed., pp. 97–102. Cambridge, UK: Cambridge University Press.

Baras, J. D., and Baker, L. C. (2009). Magnetic resonance imaging and low back pain care for Medicare patients.

Ganapathy, A. (2015). AI Fitness Checks, Maintenance and Monitoring on Systems Managing Content & Data: A Study on CMS World. Malaysian Journal of Medical and Biological Research, 2(2), 113-118. https://doi.org/10.18034/mjmbr.v2i2.553

Ganapathy, A. (2016). Speech Emotion Recognition Using Deep Learning Techniques. ABC Journal of Advanced Research, 5(2), 113-122. https://doi.org/10.18034/abcjar.v5i2.550

Seligman, B., Tuljapurkar, S. and Rehkopf, D. (2017). Machine learning approaches to the social determinants of health in the health and retirement study. SSM-Population Health 4:95–99.

Skloot, R. 2011. The Immortal Life of Henrietta Lacks. New York: Broadway Books. Sonka, M., V. Hlavac, and R. Boyle. (2008). Image Processing, Analysis, and Machine Vision. 4th ed. Boston, MA: Cengage Learning.

Sun, C., Shrivastava, A. Singh, S. and Gupta, A. (2017). Revisiting Unreasonable effectiveness of data in the deep learning era. https://arxiv.org/pdf/1707.02968.pdf.

Tan Zhong, Ji., Zhiqiang, Z., and Yan-bin, S. (2012). The overview of the health management system. https://sciencedirect.com

Vadlamudi, S. (2015). Enabling Trustworthiness in Artificial Intelligence - A Detailed Discussion. Engineering International, 3(2), 105-114. https://doi.org/10.18034/ei.v3i2.519

Vadlamudi, S. (2016). What Impact does Internet of Things have on Project Management in Project based Firms?. Asian Business Review, 6(3), 179-186. https://doi.org/10.18034/abr.v6i3.520

Vadlamudi, S. (2017). Stock Market Prediction using Machine Learning: A Systematic Literature Review. American Journal of Trade and Policy, 4(3), 123-128. https://doi.org/10.18034/ajtp.v4i3.521

Zarsky, T. (2016). The trouble with algorithmic decisions: An analytic road map to examine efficiency and fairness in automated and opaque decision making. Science, Technology, & Human Values 41(1): 118-132.

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Published

2018-12-31

Issue

Section

Peer-reviewed Article

How to Cite

Paruchuri, H. (2018). AI Health Check Monitoring and Managing Content Up and Data in CMS World. Malaysian Journal of Medical and Biological Research, 5(2), 141-146. https://doi.org/10.18034/mjmbr.v5i2.554