期刊名称：International Journal of Advanced Computer Science and Applications(IJACSA)
印刷版ISSN：2158-107X
电子版ISSN：2156-5570
出版年度：2017
卷号：8
期号：10
DOI：10.14569/IJACSA.2017.081056
出版社：Science and Information Society (SAI)
摘要：The objective of this research study is to validate Indian Weighted Diabetes Risk Score (IWDRS). The IWDRS is derived by applying the novel concept of semantic discretization based on Data Mining techniques. 311 adult participants (age > 18 years), who have been tested for diabetes using the biochemical test in pathology laboratory according to World Health Organization (WHO) guidelines, were selected for this study. These subjects were not included for deriving IWDRS tool. IWDRS is calculated for all 311 subjects. Prediction parameters, such as sensitivity and specificity are evaluated along with other performance parameters for an optimal cut-off score for IWDRS. The IWDRS tool is validated and found to be highly sensitive in diagnosing diabetes positive cases at the same time it is almost equally specific for identifying diabetes negative cases as well. The result of IWDRS is compared with the results of another two similar studies conducted for the Indian population and found it better. At optimal cut-off score IWDRS>=294, the prediction accuracy is 82.32%, while sensitivity and specificity is 82.22% and 82.44%, respectively.
