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Designing an automated system for medical diagnosis

Author: Parekh, Ranjan

Keywords: Medical diagnosis
Medical offices--Automation

Issue Date: 2012-01

Publisher: National Council of Science Museums, Kolkata

Description: This paper proposes an automated system for recognizing disease conditions of human skin in context to health informatics. Skin texture images, displaying three dermatological skin conditions, are analyzed using a texture analysis technique, based on a set of normalized symmetrical Grey Level Occurrence Matrices (GLCM), and features are extracted from them using automated algorithms. The features are Jed to neural network classifiers for identification of the disease type. The features are considered in various combinations viz. individually, in joint 2-D and 3-D feature spaces, to find out the best recognition accuracies.

Description: Includes bibliographical references.

Source: National Council of Science Museums

Type: Article

Received From: National Council of Science Museums


DC Field Value
dc.contributor.author Parekh, Ranjan
dc.date.accessioned 2017-06-15T11:06:07Z
dc.date.available 2017-06-15T11:06:07Z
dc.description Includes bibliographical references.
dc.date.issued 2012-01
dc.description.abstract This paper proposes an automated system for recognizing disease conditions of human skin in context to health informatics. Skin texture images, displaying three dermatological skin conditions, are analyzed using a texture analysis technique, based on a set of normalized symmetrical Grey Level Occurrence Matrices (GLCM), and features are extracted from them using automated algorithms. The features are Jed to neural network classifiers for identification of the disease type. The features are considered in various combinations viz. individually, in joint 2-D and 3-D feature spaces, to find out the best recognition accuracies.
dc.source National Council of Science Museums
dc.format.extent 57-64p.: col.ill.
dc.format.mimetype application/pdf
dc.language.iso en
dc.publisher National Council of Science Museums, Kolkata
dc.subject Medical diagnosis
Medical offices--Automation
dc.type Article
dc.identifier.issuenumber 1
dc.format.medium text
DC Field Value
dc.contributor.author Parekh, Ranjan
dc.date.accessioned 2017-06-15T11:06:07Z
dc.date.available 2017-06-15T11:06:07Z
dc.description Includes bibliographical references.
dc.date.issued 2012-01
dc.description.abstract This paper proposes an automated system for recognizing disease conditions of human skin in context to health informatics. Skin texture images, displaying three dermatological skin conditions, are analyzed using a texture analysis technique, based on a set of normalized symmetrical Grey Level Occurrence Matrices (GLCM), and features are extracted from them using automated algorithms. The features are Jed to neural network classifiers for identification of the disease type. The features are considered in various combinations viz. individually, in joint 2-D and 3-D feature spaces, to find out the best recognition accuracies.
dc.source National Council of Science Museums
dc.format.extent 57-64p.: col.ill.
dc.format.mimetype application/pdf
dc.language.iso en
dc.publisher National Council of Science Museums, Kolkata
dc.subject Medical diagnosis
Medical offices--Automation
dc.type Article
dc.identifier.issuenumber 1
dc.format.medium text