SkinDiRecT: Skin disease recognition

Authors

Lance Edward T. Lim, De La Salle University, Manila
Eliel Jan O. Sarmiento, De La Salle University, Manila
Billy Andrew G. Sy, De La Salle University, Manila
Lou Allen M. UySison, De La Salle University, Manila
Rigan P. Ap-apid, De La Salle University, Manila

College

College of Computer Studies

Department/Unit

Software Technology

Document Type

Archival Material/Manuscript

Publication Date

2007

Abstract

Research in the field of decision-support in medicine has paved the way to the advent of new approaches to medical diagnoses. This concept of storing prior knowledge of the features of a disease into a system and enabling it to automate the evaluation process has significantly minimized the amount of time required to diagnose certain disorders and noticeably improved the accuracy of diagnoses. This paper presents a system, which uses image pattern recognition techniques to identify or recognize skin diseases from image inputs. The accuracy of the automated diagnosis reached a high of 93.16%.

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Recommended Citation

Lim, L. T., Sarmiento, E. O., Sy, B. G., UySison, L. M., & Ap-apid, R. P. (2007). SkinDiRecT: Skin disease recognition. Retrieved from https://animorepository.dlsu.edu.ph/faculty_research/12586

Disciplines

Computer Sciences

Note

Undated; Publication/creation date supplied

Keywords

Pattern recognition systems; Skin--Diseases

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