A novel algorithm based on information diffusion and fuzzy MADM methods for analysis of damages caused by diabetes crisis

Abstract Diabetes mellitus is one of the most common chronic diseases in the world. A remarkable point about chronic diseases is that patients may be involved in related complications throughout their lifetime. Management and control of chronic diseases are one of the most costly and important issues in the healthcare field due to their long term treatment period. In this paper, the number of patients involved in complications of type II diabetes has been studied in 19 years and the goal is to calculate the severity of damage caused by diabetes by a new hybrid algorithm which is consisted of multi criteria decision making, variable fuzzy set theory and information diffusion method for the first time. However, the traditional probability statistical methods ignore the fuzziness of risk assessment with incomplete data sets and require a large sample size of data, the new proposed algorithm deals effectively with these challenges and produces more accurate results with fewer errors. For example in terms of working with small data samples, it will be shown that the mean error of results produced by hybrid algorithm is 0.0198 while it is 0.0264 for multiple regression and 0.0299 for cox proportional hazard method which means 33.3% and 51% error increase in proportion to hybrid algorithm respectively.

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