Open AccessDetermination of Hazard State of Non-Communicable Diseases Using Semi-Markov Model
Author(s) -
Balasubramaniam Ramakrishnan,
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Senthamarai Kannan Kaliyaperumal,
Mahalakshmi Rajendran,
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Publication year - 2021
Publication title -
international journal of medical sciences and nursing research
Language(s) - English
Resource type - Journals
ISSN - 2583-0996
DOI - 10.55349/ijmsnr.2021122328
Subject(s) - statistics , rayleigh distribution , markov chain , markov model , mathematics , hidden markov model , hazard , exponential distribution , medicine , econometrics , computer science , probability density function , artificial intelligence , chemistry , organic chemistry
Background: The developed Semi-Markov model with Kumaraswamy Exponentiated Inverse Rayleigh distribution examined patients with hypertension, heart diseases, smoking habits and Stroke, is measured from one state to another. Materials and Methods: Patients with Non-Communicable disease described through Kumaraswamy Exponentiated Inverse Rayleigh distribution. Results: The estimated parameters of Semi-Markov model with this distribution predicted by the maximum likelihood estimation for each successive state observed significant abnormality. The data noted predicts established model is a good fit for many attributes that prevailed in studied data. The developed Semi-Markov model is a best fit for non-Communicable disease in the long run of patient’s data. Through different Exponential family distribution, one can look at for further perfect fit of patient data, which is to be estimated. Conclusion: This model can be an alternative method to estimate the effect of patient in survival analysis, where it will be effective in time consumption in medical field. Keywords: heart diseases, hypertension, Semi-Markov processes, smoking, stroke.