Please use this identifier to cite or link to this item:
https://hdl.handle.net/10216/90532
Author(s): | Sk. Saddam Ahmed Nilanjan Dey Amira S. Ashour Dimitra Sifaki-Pistolla Dana Balas-Timar Valentina E. Balas João Manuel R. S. Tavares |
Title: | Effect of fuzzy partitioning in Crohn's disease classification: a neuro-fuzzy-based approach |
Issue Date: | 2017-01 |
Abstract: | Crohn's disease (CD) diagnosis is a tremendously serious health problem due to its ultimately effect on the gastrointestinal tract that leads to the need of complex medical assistance. In this study, the backpropagation neural network fuzzy classifier and a neuro-fuzzy model are combined for diagnosing the CD. Factor analysis is used for data dimension reduction. The effect on the system performance has been investigated when using fuzzy partitioning and dimension reduction. Additionally, further comparison is done between the different levels of the fuzzy partition to reach the optimal performance accuracy level. The performance evaluation of the proposed system is estimated using the classification accuracy and other metrics. The experimental results revealed that the classification with level-8 partitioning provides a classification accuracy of 97.67 %, with a sensitivity and specificity of 96.07 and 100 %, respectively. |
Subject: | Ciências Tecnológicas, Ciências médicas e da saúde Technological sciences, Medical and Health sciences |
Scientific areas: | Ciências médicas e da saúde Medical and Health sciences |
URI: | https://hdl.handle.net/10216/90532 |
Document Type: | Artigo em Revista Científica Internacional |
Rights: | openAccess |
Appears in Collections: | FEUP - Artigo em Revista Científica Internacional |
Files in This Item:
File | Description | Size | Format | |
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171381.pdf | Draft | 762.65 kB | Adobe PDF | View/Open |
171381.1.png | 1st Page | 349.03 kB | image/png | View/Open |
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