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- W3180884092 abstract "The analysis of feature space plays a vital role in making valid decisions in the bio-medical domain. In this article, we have investigated the feature space of laboratory tests conducted to diagnose “Cystitis” and “Nephritis”. The experimentation samples were acquired from laboratory reports generated at Sharda Hospital. Moreover, the feature space analysis is conducted using K-Means clustering and Neural Networks in an unsupervised mode. The experimental outcomes are promising in nature to understand the disease’s feature space that enhances the decision making." @default.
- W3180884092 created "2021-07-19" @default.
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- W3180884092 date "2018-01-01" @default.
- W3180884092 modified "2023-09-23" @default.
- W3180884092 title "An Unsupervised Learning Approach to Analyze the Feature Space of Cystitis and Nephritis" @default.
- W3180884092 hasPublicationYear "2018" @default.
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