A hybrid intelligent system for skin disease diagnosis

Nisreen I.Abo Dabowsa, Nasser M. Amaitik, Abdelsalam M. Maatuk, Shadi A. Aljawarneh

Research output: Chapter in Book/Published conference outputConference publication

Abstract

In this paper, an intelligent decision support system has been proposed for skin disease diagnosis using a hybrid model of Case-Based Reasoning and Artificial Neural Network techniques. The proposed model uses nine input variables (attributes) that have a major effect on the skin diagnosing process. The output of the model is the diagnosis and the treatment. An interactive and user friendly computer application has been developed in order to realize the approach. We have applied the system on a real-world data collected from a dermatology department. The model has been validated and the system tested using a separate set of data (test cases). The results demonstrate that the proposed intelligent system is feasible, and its performance is good and acceptable.

Original languageEnglish
Title of host publicationProceedings of 2017 International Conference on Engineering and Technology, ICET 2017
PublisherIEEE
Pages1-6
Number of pages6
ISBN (Electronic)9781538619490
DOIs
Publication statusPublished - 7 Mar 2018
Event2017 International Conference on Engineering and Technology, ICET 2017 - Antalya, Turkey
Duration: 21 Aug 201723 Aug 2017

Publication series

NameProceedings of 2017 International Conference on Engineering and Technology, ICET 2017
Volume2018-January

Conference

Conference2017 International Conference on Engineering and Technology, ICET 2017
CountryTurkey
CityAntalya
Period21/08/1723/08/17

Keywords

  • ANN
  • CBR
  • diseases diagnosis
  • intelligent system

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