NDLI: A hybrid Decision Support System for the risk assessment of retinopathy development as a long term complication of Type 1 Diabetes Mellitus

Content Provider	IEEE Xplore Digital Library
Author	Skevofilakas, M. Zarkogianni, K. Karamanos, B.G. Nikita, K.S.
Copyright Year	2010
Description	Author affiliation: Diabetes Centre, Hippokration Hospital, V. Sofias 114,11527, Athens, Greece (Karamanos, B.G.) \|\| School of Electrical and Computer Engineering, National Technical University of Athens, 9 Heroon Polytechneiou Str., 15780 Zografou, Greece (Skevofilakas, M.; Zarkogianni, K.; Nikita, K.S.)
Abstract	The aim of the present study is to design and develop a Decision Support System (DSS) closely coupled with an Electronic Medical Record (EMR), able to predict the risk of a Type 1 Diabetes Mellitus (T1DM) patient to develop retinopathy. The proposed system is able to store a wealth of information regarding the clinical state of the T1DM patient and continuously provide the health experts with predictions regarding the possible future complications that he may present. The DSS is a hybrid infrastructure combining a Feedforward Neural Network (FNN), a Classification and Regression Tree (CART) and a Rule Induction C5.0 classifier, with an improved Hybrid Wavelet Neural Network (iHWNN). A voting mechanism is utilized to merge the results from the four classification models. The proposed DSS has been trained and evaluated using data from 55 T1DM patients, acquired by the Athens Hippokration Hospital in close collaboration with the EURODIAB research team. The DSS has shown an excellent performance resulting in an accuracy of 98%. Care has been taken to design and implement a consistent and continuously evolving Information Technology (IT) system by utilizing technologies such as smart agents periodically triggered to retrain the DSS with new cases added in the data repository.
Starting Page	6713
Ending Page	6716
File Size	350541
Page Count	4
File Format	PDF
ISBN	9781424441235
ISSN	1557170X
DOI	10.1109/IEMBS.2010.5626245
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-08-31
Publisher Place	Argentina
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Diabetes Decision support systems Retinopathy Classification algorithms Artificial neural networks Sugar Accuracy
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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