Update and Acceleration of Health Care Using Artificial Intelligence in Medical Treatments and Diagnostics
DOI:
https://doi.org/10.14738/assrj.812.11425Keywords:
Data analytics; Artificial intelligence; (AI) Autoregressive moving average Modeling; Machine Learning; Multivariate Models; Autocorrelation of DataAbstract
Abstract
Researchers support the growth of artificial intelligence and similar methods in health and medical care for the purpose of continuously improving processes. By focusing on the growth on data analytics, statistics, applied mathematics, and computer methods including machine learning, the future of health-care methods will change. The development of computerized methods and the growth of data systems produce ample materials for artificial intelligence to develop and to bring physician assistance programs to enable continuous improvement resulting in superior health and medical care. This includes applications in intensive care as well as diagnostic therapies. The focus is on examples in the use of the promising developments in data science methods, the accumulation of medical and research data. With quality and continuous improvement in process control applications where one determines the usefulness of data analytics, there are great possibilities of change in the improvement in medical applications as well as the management of medical and health-care treatment and diagnostic facilities.
References
References
Acampora, G., Cook, D.J., Rashidi, P., and Vasilakos, A.V. (2013). “A Survey on Ambient Intelligence in Healthcare.” Proceedings of the IEEE, 101, 2470–2494. Doi: 10.1109/JPROC.2013.2262913.
Alwan, L.C. (1992). “Time-Series Investigation of Subsample Mean Charts.” Communications in Statistics—Theory and Methods, 21 (4), 1025–1049.
Alwan, L.C. (2000). Statistical Process Control. New York: Irwin-McGraw-Hill.
Atienza, O.O., Tang, L.C., and Ang, B.W. (1998). “A SPC Procedure for Detecting Level Shifts of Autocorrelated Processes.” Journal of Quality Technology, 30, 340–351.
Berthouex, P.M., Hunter, E., and Pallesen, I. (1978). “Monitoring Sewage Treatment Plants, Some Quality Control Aspects.” Journal of Quality Technology, 10 (4), 149–159
Box, G.E.P., and Draper, N.R. (1998). Empirical Model Building and Response Surfaces. New York: Wiley.
Box, G.E.P., Jenkins, G.M., and Reinsel, G.C. (2008). Time Series Analysis, Forecasting and Control, 4th Ed. New York: Wiley.
Cambria, E., and White, B. (2014). “Jumping NLP Curves: A Review of Natural Language Processing Research [Review Article].” IEEE Computational Intelligence Magazine, 9 (2), 48–57. doi: 10.1109/MCI.2014.2307227.
Elsayed, E.A., and Sastri, T. (2007). “Design of Optimum Simple Step-Stress Accelerated Life Testing Plans.” Recent Advancement of Stochastic Operations Research, edited by S. Dohl, T.S. Osaki, and K. Sawaki. Singapore: World Scientific.
Griggs, O.A., and Spiegalhalter, D.J. (2007). “A Simple Risk-Adjusted Exponentially Weighted Moving Average.” Journal of the American Statistical Association, 102 (477), 140–152.
Hanson, C., and Marshall, B. (2001). “Artificial Intelligence Applications in the Intensive Care Unit.” Critical Care Medicine, 29 (2), 427–435.
Jarrett, J.E. (2016a). “Total Quality Management (TQM) Movement in Public Health.” International Journal of Quality & Reliability, 33 (1), 25–41. Doi: 10.1108/IJQRM-12-2013-0193.
Jarrett, J.E. (2016b). “Data Analytics and Managing Health and Medical Care.” Global Journal of Human Social Sciences, 16 (4), 17–24.
Jarrett, J.E., and Pan, X. (2006). “The Quality Control Chart for Monitoring Multivariate Autocorrelated Processes.” Computational Statistics and Data Analysis, 51, 38621–38700.
Jarrett, J.E., and Pan, X. (2007a). “Using Vector Autoregressive Residuals to Monitor Multivariate Processes in the Presence of Serial.” International Journal of Production Economics, 106, 204–216.
Jarrett, J.E., and Pan, X. (2007b). “Monitoring Variability and Analyzing Multivariate Processes.” Journal of Applied Statistics, 34 (4), 459–469.
Jarrett, J.E., and Pan, X. (2013). “Constructing SPC Charts by Cumulative Square and Cumulative Variance Methodologies.” International Journal of Management and Industrial Engineering, 3 (6), 247–253.
Jarrett, J.E., and Pan, X. (2015). “The Multivariate EWMA Model and Monitoring Bio Surveillance.” International Journal of Advances in Management, Economics and Entrepreneurship, 2 (12), 1–6.
Kalagonda, A.A., and Kulkarni, S.R. (2003). “Diagnoses of Multivariate Control Chart Signal for Autocorrelated Processes.” Communications in Statistics—Theory and Methods, 14 (110), 2657–2688.
Kalagonda, A.A., and Kulkarni, S.R. (2004). “Multivariate Quality Control for Autocorrelated Processes.” Journal of Applied Statistics, 31 (3), 317–327.
Khoo, M.B.C., and Quah, S.H. (2003). “Incorporating Runs Rules into Hotelling’s χ2 Control Charts.” Quality Engineering, 15 (4), 671–675.
Lee, H.L., and Wang, S. (2003). “Higher Supply Chain Security and Lower Cost Lessons from Total Quality Management.” Research Paper No. 1824, Stanford Graduate School of Business, Palo Alto, CA.
Liu, N.T., and Salinas, J. (2017). “Machine Learning for Predicting Outcomes in Trauma.” Shock, 48 (5), 504–510. Doi: 10.1097/SHK.0000000000000898.
Marques, I., Captivo, M.E., and Vaz Pato, M. (2014). “Scheduling Elective Surgeries in a Portuguese Hospital Using a Genetic Heuristic.” Operations Research in Health Care, 3 (2), 59–72.
Montgomery, D.C. (2013). Introduction to Statistical Quality Control, 7th Ed. New York: Wiley.
Montgomery, D.C., and Mastrangelo, G.C. (1991). “Statistical Quality Control in a Computer-Integrated Manufacturing Environment.” Statistical Process Control in Automated Manufacturing, edited by J. Kates and N. Hunele. New York: Marcel Decker.
Patel, V.L., Shortliffe, E.H, Stefanelli, M., Szolovits, P., Berthold, M.R., Bellazzi, R., and Abu-Hanna, A. (2009). “Coming of Age of Artificial Intelligence in Medicine.” Artificial Intelligence in Medicine, 46 (1), 5–17.
Radiol. 2019 Aug; 92(1100): 20190001. Published online 2019 Jun 3. Doi: 10.1259/bjr.20190001
Vanhatalo, E., and Kulachi, M. (2015). “The Effect of Autocorrelation on the Hotelling T2 Control Chart.” Quality and Reliability Engineering International, 31 (8), 1779–1796.
Weihs, C., and Jessenberger, J. (1999). “Statistische Methoden zur Qualitætssicherungen und Optimierungen.” Statistica Neerlandica, 48, 147–168.
West, D., Dellana, S., and Jarrett, J.E. (2002). “Transfer Function Modeling with Dynamic Inputs.” Journal of Quality Technology, 34 (3), 315–326.
Woodall, W.H. (2005). “The Use of Control-Charts in Health Care Public Health Surveillance.” Journal of Quality Technology, 38 (2), 89–104.
Yang, S.F., and Rahim, R.A. (2005). “Economics Statistical Process Control for Multivariate Quality Characteristics under Weibel Shock Model.” International Jordan of Production Economics, 98, 215–226.
Yeh, A.B., Hwang, L., and Wu, Y. (2004). “A Likelihood-Ratio-Based EWMA Chart for Monitoring Variability of Multivariate Normal Processes.” IIE Transactions, 36, 863–879.
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