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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Computer Science and Information Technologies
Rahmat Budiarto
Universitas Mercu Buana
Computer Science & IT Engineering

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Journal : IAES International Journal of Artificial Intelligence (IJ-AI)

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Neural network models selection scheme for health mobile app development Yaya Sudarya Triana; Mohd Azam Osman; Adji Pratomo; Muhammad Fermi Pasha; Deris Stiawan; Rahmat Budiarto
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 12, No 3: September 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v12.i3.pp1191-1203

Abstract

Mobile healthcare application (mHealth app) assists the frontline health worker in providing necessary health services to the patient. Unfortunately, existing mHealth apps continue to have accuracy issues and limited number of disease detection systems. Thus, an intelligent disease diagnostics system may help medical staff as well as people in poor communities in rural areas. This study proposes a scheme for simultaneously selecting the best neural network models for intelligent disease detection systems on mobile devices. To find the best models for a given dataset, the proposed scheme employs neural network models capable of evolving altered neural network architectures. Eight neural network models are developed simultaneously and then implemented on the Android Studio platform. Mobile health applications use pre-trained neural network models to provide users with disease prediction results. The performance of the mobile application is measured against the existing available datasets. The trained neural network engines perform admirably, detecting 7 out of 8 diseases with high accuracy ranging from 86% to 100% and a low detection accuracy of 63%. The detection times vary from 0.01 to 0.057 seconds. The developed mHealth app may be used by health workers and patients to improve resource-poor community health services and patients' healthcare quality.
Co-Authors Adji Pratomo Deris Stiawan Ifan Prihandi Lindo Prasetyo Mohd Azam Osman Muhammad Fermi Pasha Muhammad Rifqi Yaya Sudarya Triana