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Abstract

Medicinal services are one of the prime worries of each individual. This work deals with diabetes, an incessant illness which is exceptionally regular throughout the world. Administration of such complex ailments requires proper diagnosis for which efficient analysis is required. So, extracting the diabetes reports in productive way is an essential concern. The Pima Indian Diabetes Data Set is used for this project, which accumulates the data of individuals who are affected and not affected by diabetes. The work goes for discovering solutions to analyze the illness by looking at patterns found in the information through classification analysis. The altered J48 classifier is applied to enhance the precision rate before which preprocessing and feature selection have been done as this prompts to decisions which are more accurate. The research would like to promote an agile and more proficient method of diagnosing the malady, prompting better treatment of the patients.

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Acknowledgements

The proposed research work has been funded under DRDO-LSRB (DRDO-Life Science Research Board)—No. CC R&D (TM)/81/48222/LSRB-284.

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Correspondence to N. Managathayaru .

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Managathayaru, N. et al. (2020). Diagnosis of Diabetes Using Clinical Decision Support System. In: Raju, K., Govardhan, A., Rani, B., Sridevi, R., Murty, M. (eds) Proceedings of the Third International Conference on Computational Intelligence and Informatics . Advances in Intelligent Systems and Computing, vol 1090. Springer, Singapore. https://doi.org/10.1007/978-981-15-1480-7_29

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