Methodological Development of Mathematical Modeling Techniques in Health Care
V. J. Chakravarthy1, P. Hakkim Devan Mydeen2, M. Seenivasan3
1M. Seenivasan*, Department of Mathematics, Annamalai University, Annamalai Nagar, Tamil Nadu, India.
2V. J. Chakravarthy, P. G. Department of Computer Science, The New College, Chennai, Tamil Nadu, India.
3P. Hakkim Devan Mydeen, P. G. Department of Computer Science, The New College, Chennai, Tamil Nadu, India.
Manuscript received on December 18, 2019. | Revised Manuscript received on December 25, 2019. | Manuscript published on January 10, 2020. | PP: 3339-3342 | Volume-9 Issue-3, January 2020. | Retrieval Number: C8862019320/2020©BEIESP | DOI: 10.35940/ijitee.C8862.019320
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The advancement of mathematical model has utilized for simulating the output of medical is a development area over medicine whereas the modeling can be mentioned with several activities namely simulation or decision analysis and predictive modeling. However, the traditional modeling technique utilized in planning of health service, assessment reports and its efficiency, financing about health care and assessment in budget impact, assessment in health economics, surveillance of infectious disease and other health care application. Therefore, the mathematical modelling is performed as a frequent and timely benefit in order to make rapid decision making while facing investigation with several issues like time elapsing, unusual and unethical particularly projected for future. This paper focused in applying the mathematical modeling to accomplish an optimal decision making in healthcare whereas this study discuss about the specific modeling concepts namely decision tree and fuzzified rule tables on evaluation of health economics and better service planning that my replicate the individual experience or patients cohorts.
Keywords: Health Care, Mathematical Modelling, Medicine, Patients
Scope of the Article: Healthcare Informatics