Design of an Expert System for Mitigating Trace Element Toxicity in Cancer Risk Management
Author(s) -
P.T. Krishna Kumar,
Priya Vinod,
Vir V. Phoha,
S. S. Iyengar,
Puneeth Iyengar
Publication year - 2013
Publication title -
cancer informatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.606
H-Index - 31
ISSN - 1176-9351
DOI - 10.4137/cin.s10770
Subject(s) - trace (psycholinguistics) , trace element , toxicity , cancer , computer science , toxicology , risk analysis (engineering) , chemistry , medicine , biology , organic chemistry , philosophy , linguistics
Cancer risk management involves obliterating excess concentration of cancer causing trace elements by the natural immune system and hence intake of nutritious diet is of paramount importance. Human diet should consist of essential macronutrients that have to be consumed in large quantities and trace elements are to be consumed in very little amount. As some of these trace elements are causative factors for various types of cancer and build up at the expense of macronutrients, cancer risk management of these trace elements should be based on their initial concentration in the blood of each individual and not on their tolerable upper intake level. We propose an information theory based Expert System (ES) for estimating the lowest limit of toxicity association between the trace elements and the macronutrients. Such an estimate would enable the physician to prescribe required medication containing the macronutrients to annul the toxicity of cancer risk trace elements. The lowest limit of toxicity association is achieved by minimizing the correlated information of the concentration correlation matrix using the concept of Mutual Information (MI) and an algorithm based on a Technique of Determinant Inequalities (TDI) developed by the authors. The novelty of our ES is that it provides the lowest limit of toxicity profile for all trace elements in the blood not restricted to a group of compounds having similar structure. We demonstrate the superiority our algorithm over Principal Component Analysis in mitigating trace element toxicity in blood samples.
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