Abstract
This study aimed at proposing a basic health screening system based on data mining techniques in order to help related personnel on basic health screening and to facilitate citizens on self-examining health conditions. The research comprised of two steps. The first step was to create a model by using classification techniques that are Bayesian methods (Naive Bayes, Bayesian networks, and Naive Bayesian Updateable) and decision tree methods (C4.5, ID3, Partial Rule) to find important attributes causing the disease. In this step, the accuracy of each method was compared to the other methods to select the most efficient model as an input for the next step. The second step was to develop a basic health screening system by exploiting rules from the model developed in the first step as the second step’s inputs were to classify from a citizen’s health profile whether a given citizen is in a normal group, risk group or sick group. Research findings revealed two important attributes directly contributing to diabetes: Blood pressure (BP) and docetaxel (DTX). Furthermore, C4.5 algorithm provided the most accuracy with accuracy of 99.7969%, precision of 99.8%, recall of 99.8% and F-measure of 99.8%.
Highlights
According to 2015 global diabetes statistics, it revealed that more than 415 million people were diabetic patients and it is expected that by 2045, the number of diabetic patients would reach 642 million people and the trend is increasing going forward
The researchers presented the experiment into two parts: the first part was the result of model building based on classification techniques and development of basic health screening system based on data mining techniques
The accuracy comparison result from experimentation using classification techniques is shown in Table 3, which reveals that a model created from decision tree methods have higher accuracy for classification as a normal group, risk group or sick group than a model created from Bayesian methods
Summary
According to 2015 global diabetes statistics, it revealed that more than 415 million people were diabetic patients and it is expected that by 2045, the number of diabetic patients would reach 642 million people and the trend is increasing going forward. One-eleventh of people were unexpectedly affected by diabetes, and one-seventh of birth was affected by diabetes during pregnancy, and one person will pass away from diabetes in every 6 seconds. Diabetic patients are in the risk of hypertension and other serious complications.1 If this disease is not well addressed, mortality and morbidity rate will increase as well as increasing financial burden and the economic loss will impact to the nation. Diabetes is the outcome of risk behaviors, including over consumption of sweet, oily and salty foods, under consumption of vegetables
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