Insulin Chart Prediction for Diabetic Patients Using Hidden Markov Model (HMM) and Simulated Annealing Method

Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 236)

Abstract

Most of the diabetic patients need to take insulin before every meal. The doctors have to decide insulin doses for every patient according to the patient’s previous records of doses and sugar levels measured at regular intervals. This paper proposes a hidden Markov model to predict the insulin chart for a patient and uses simulated annealing search algorithm to efficiently implement the model. The one-month chart maintained by the patient has been used to train the model, and the prediction for next fifteen days is done on the basis of the trained data. We discussed the results with the university medical doctor; he was very pleased to see to the result obtained.

Keywords

Hidden Markov model (HMM) Randomized algorithm (RA) Simulated annealing (SA) Diabetic patient chart prediction (DPCP) 

Notes

Acknowledgments

The authors of the paper are highly grateful to Dr. Chaman Kumar (MBBS, MD), CSJM University, Kanpur, for discussing the results with us and encouraging us to do more work in this direction.

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Copyright information

© Springer India 2014

Authors and Affiliations

  1. 1.Department of Computer Science and EngineeringUniversity Institute of Engineering and Technology, Chattrapati Shahuji Maharaj UniversityKanpurIndia

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