Diagnosing diabetes using neural networks on small mobile devices

Authors:
Oğuz Karan;Canan Bayraktar;Haluk Gümüşkaya;Bekir Karlık
Affiliations:
Haliç University, Department of Computer Engineering, Şişli, İstanbul, Turkey;Haliç University, Department of Computer Engineering, Şişli, İstanbul, Turkey;Gediz University, Department of Computer Engineering, Menemen, İzmir, Turkey;Mevlana University, Department of Computer Engineering, Selçuklu, Konya, Turkey
Venue:
Expert Systems with Applications: An International Journal
Year:
2012

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Abstract

Pervasive computing is often mentioned in the context of improving healthcare. This paper presents a novel approach for diagnosing diabetes using neural networks and pervasive healthcare computing technologies. The recent developments in small mobile devices and wireless communications provide a strong motivation to develop new software techniques and mobile services for pervasive healthcare computing. A distributed end-to-end pervasive healthcare system utilizing neural network computations for diagnosing illnesses was developed. This work presents the initial results for a simple client (patient's PDA) and server (powerful desktop PC) two-tier pervasive healthcare architecture. The computations of neural network operations on both client and server sides and wireless network communications between them are optimized for real time use of pervasive healthcare services.