EAGA-MLP-An Enhanced and Adaptive Hybrid Classification Model for Diabetes Diagnosis.

Sensors
Sushruta MishraPaolo Barsocchi

Abstract

Disease diagnosis is a critical task which needs to be done with extreme precision. In recent times, medical data mining is gaining popularity in complex healthcare problems based disease datasets. Unstructured healthcare data constitutes irrelevant information which can affect the prediction ability of classifiers. Therefore, an effective attribute optimization technique must be used to eliminate the less relevant data and optimize the dataset for enhanced accuracy. Type 2 Diabetes, also called Pima Indian Diabetes, affects millions of people around the world. Optimization techniques can be applied to generate a reliable dataset constituting of symptoms that can be useful for more accurate diagnosis of diabetes. This study presents the implementation of a new hybrid attribute optimization algorithm called Enhanced and Adaptive Genetic Algorithm (EAGA) to get an optimized symptoms dataset. Based on readings of symptoms in the optimized dataset obtained, a possible occurrence of diabetes is forecasted. EAGA model is further used with Multilayer Perceptron (MLP) to determine the presence or absence of type 2 diabetes in patients based on the symptoms detected. The proposed classification approach was named as Enhanced and Adaptiv...Continue Reading

References

Jun 10, 2006·IEEE Transactions on Bio-medical Engineering·Paolo Magni, Riccardo Bellazzi
Nov 1, 2006·IEEE Transactions on Bio-medical Engineering·D U Campos-DelgadoA Gordillo-Moscoso
May 27, 2010·IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the IEEE Systems, Man, and Cybernetics Society·Chang-Shing Lee, Mei-Hui Wang
Aug 13, 2013·Computer Methods and Programs in Biomedicine·Fayssal Beloufa, M A Chikh
Feb 27, 2018·Computer Methods and Programs in Biomedicine·Piyush Samant, Ravinder Agarwal

❮ Previous
Next ❯

Citations

Jun 18, 2021·Computers in Biology and Medicine·Satish Kumar KalagotlaKanuri Giridhar

❮ Previous
Next ❯

Software Mentioned

GeneticSearch
MLP
Waikato Environment for Knowledge Analysis ( WEKA )
Java
EAGA
Windows
JFreeChartis
ISS
Extreme
Comp

Related Concepts

Related Feeds

CREs: Gene & Cell Therapy

Gene and cell therapy advances have shown promising outcomes for several diseases. The role of cis-regulatory elements (CREs) is crucial in the design of gene therapy vectors. Here is the latest research on CREs in gene and cell therapy.