Markov Chain Monte Carlo based Pattern Analysis for Diabetic Spectral Data

C  Dharuman   and P  Venkatesan

doi:10.17485/ijst/2015/v8i33/77184

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Markov Chain Monte Carlo based Pattern Analysis for Diabetic Spectral Data

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Indian Journal of Science and Technology

DOI: 10.17485/ijst/2015/v8i33/77184

Year: 2015, Volume: 8, Issue: 33, Pages: 1-4

Original Article

Markov Chain Monte Carlo based Pattern Analysis for Diabetic Spectral Data

C. Dharuman^1* and P. Venkatesan²

¹SRM University, Ramapuram Campus, Chennai - 600089, Tamil Nadu, India; [email protected]
² Sri Ramachandra University, Porur, Chennai - 600116, Tamil Nadu, India; [email protected]

This work is licensed under a Creative Commons Attribution 4.0 International License.

Abstract

Markov Chain Monte Carlo (MCMC) methods have been successfully used to overcome problems involving high dimensional diabetic spectral data. The objective is to show that the onset of a disease changes the relative content of the Bio-Molecules. The problem is formulated and solved in Bayesian frame work by using MCMC algorithm. The efficiency of the models are discussed, evaluated and compared.
Keywords: Bayesian, Diabetic Spectral Data, Markov Chain Monte Carlo, Pattern Analysis