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An Analysis of Artificial Intelligence Clinical Decision-Making and Patient-Centric Framework

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Computational Vision and Bio-Inspired Computing

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1318))

Abstract

The smart decision-making support framework is typically referred to as artificial intelligence (AI). The clinical decision framework can transform the process of decision-making using various technologies. These technologies incorporate framework engineering and information technology. The vital centered ontology-centered automatic reasoning which is incorporated in machine learning methodologies has been established in the present patient databases. The approach evaluated in this paper is in the support of the interoperability between various health information systems (HIS). This has been evaluated in sampling implementations that link up to three separate databases: drug prescriptions guidelines, drug-to-drug interaction and patient information which are databases used to showcase the efficiency of an algorithm used to provide effective healthcare decisions. Generally, the possibility of artificial intelligence was evaluated in the process of supporting tasks that are essential for medical experts including the aspect of coping up with noisy and missing patient information and enhancing the utility of various healthcare datasets.

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References

  1. C. Bennett, K. Hauser, Artificial intelligence framework for simulating clinical decision-making: a Markov decision process approach. Artif. Intell. Med. 57(1), 9–19 (2013). https://doi.org/10.1016/j.artmed.2012.12.003

    Article  Google Scholar 

  2. P. Lucas, Dealing with medical knowledge: Computers in clinical decision making. Artif. Intell. Med. 8(6), 579–580 (1996). https://doi.org/10.1016/s0933-3657(97)83108-9

    Article  Google Scholar 

  3. W. Horn, Artificial intelligence in medicine and medical decision-making Europe. Artif. Intell. Med. 20(1), 1–3 (2000). https://doi.org/10.1016/s0933-3657(00)00049-x

    Article  Google Scholar 

  4. P.L. Aaron, S. Bonni, An evaluation of wearable technological advancement in medical practices. J. Med. Image Comput. 58–65 (2020)

    Google Scholar 

  5. Web based analysis of critical medical care technology. J. Med. Image Comput. 66–73 (2020)

    Google Scholar 

  6. A. Haldorai, S. Anandakumar, Image segmentation and the projections of graphic centered approaches in medical image processing. J. Med. Image Comput. 74–81 (2020)

    Google Scholar 

  7. I. Rábová, V. Konečný, A. Matiášová, Decision making with support of artificial intelligence. Agric. Econ. (Zemědělská Ekonomika) 51(9), 385–388 (2012). https://doi.org/10.17221/5124-agricecon

    Article  Google Scholar 

  8. R. Yager, Generalized regret based decision making. Eng. Appl. Artif. Intell. 65, 400–405 (2017). https://doi.org/10.1016/j.engappai.2017.08.001

    Article  Google Scholar 

  9. N.M. Hewahi, A hybrid architecture for a decision making system. J. Artif. Intell. 2(2), 73–80 (2009). https://doi.org/10.3923/jai.2009.73.80

    Article  Google Scholar 

  10. C. Gonzales, P. Perny, J. Dubus, Decision making with multiple objectives using GAI networks. Artif. Intell. 175(7–8), 1153–1179 (2011). https://doi.org/10.1016/j.artint.2010.11.020

    Article  MathSciNet  MATH  Google Scholar 

  11. Y. Chen, E. Ginell, An analysis of medical informatics and application of computer-aided decision support framework. J. Med. Image Comput. 10–17 (2020)

    Google Scholar 

  12. M. Heng Li, M. Yu Zhang, Computational benefits, limitations and techniques of parallel image processing. J. Med. Image Comput. 1–9 (2020)

    Google Scholar 

  13. R. Degani, G. Bortolan, Fuzzy decision-making in electrocardiography. Artif. Intell. Med. 1(2), 87–91 (1989). https://doi.org/10.1016/0933-3657(89)90020-1

    Article  Google Scholar 

  14. P. Giang, P. Shenoy, Decision making on the sole basis of statistical likelihood. Artif. Intell. 165(2), 137–163 (2005). https://doi.org/10.1016/j.artint.2005.03.004

    Article  MathSciNet  MATH  Google Scholar 

  15. D. McSherry, Conversational case-based reasoning in medical decision making. Artif. Intell. Med. 52(2), 59–66 (2011). https://doi.org/10.1016/j.artmed.2011.04.007

    Article  Google Scholar 

  16. T. Leong, Multiple perspective dynamic decision making. Artif. Intell. 105(1–2), 209–261 (1998). https://doi.org/10.1016/s0004-3702(98)00082-4

    Article  MATH  Google Scholar 

  17. A. Кhusein, Clinical decision support system for the activity of evidence based computation. J. Med. Image Comput. 50–57 (2020)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Sri Eshwar College of Engineering, Coimbatore, Tamil Nadu, India

    Anandakumar Haldorai

  2. Presidency University, Yelahanka, Bengaluru, Karnataka, India

    Arulmurugan Ramu

Authors
  1. Anandakumar Haldorai
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  2. Arulmurugan Ramu
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Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, RVS Technical Campus, Coimbatore, Tamil Nadu, India

    S. Smys

  2. Departamento de Engenharia Mecanica, SDI, Faculty of Engineering, Universidade do Porto, Porto, Portugal

    João Manuel R. S. Tavares

  3. Czech Technical University in Prague, Prague, Czech Republic

    Robert Bestak

  4. College of Graduate Studies, University of Central Florida, Orlando, FL, USA

    Fuqian Shi

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Haldorai, A., Ramu, A. (2021). An Analysis of Artificial Intelligence Clinical Decision-Making and Patient-Centric Framework. In: Smys, S., Tavares, J.M.R.S., Bestak, R., Shi, F. (eds) Computational Vision and Bio-Inspired Computing. Advances in Intelligent Systems and Computing, vol 1318. Springer, Singapore. https://doi.org/10.1007/978-981-33-6862-0_62

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