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http://dx.doi.org/10.7471/ikeee.2018.22.4.1093

Methodology for Implementation of the Portable Disease Diagnosis Platform based on Neural Network Using High Performance Computing  

Kim, Sang-man (Dept. of Electronics Engineering, Pusan National University)
Park, Ju-Sung (Dept. of Electronics Engineering, Pusan National University)
Publication Information
Journal of IKEEE / v.22, no.4, 2018 , pp. 1093-1098 More about this Journal
Abstract
In this paper, we proposed a methodology for portable disease diagnosis platform using high performance computing. The proposed methodology consists of gathering clinical data, diagnosis and feature selection algorithm, implementation of diagnosis platform. For the algorithm verification, a clinical data which is obtained from 401 people(314 normal subjects and 87 liver cancer patients) using a microarray consists of 1,146 aptamers were used. As the result, we could diagnosis liver cancer with 97.5% accuracy using the 32 selected aptamers. Based on these results, we designed and implemented a portable disease diagnosis platform which has 32 bio-signals as inputs.
Keywords
disease diagnosis; feature selection; neural network; high performance computing; machine learning;
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