11th Annual International Conference on Industrial Engineering and Operations Management

Designing an Android-Based Burn Rate Pattern Detection Application Model

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Track: Information Technology
Abstract

In the medical world, the role of computers in pattern recognition of a disease is very much needed. This is because if a patient experiences a disease, it can be prevented by first knowing the pattern of the disease. One of them is the initial pattern recognition of burns experienced by patients. Detecting the initial pattern of burn rates on the body will help the medical team to immediately make decisions regarding the level of burns in patients. To detect the initial pattern of burn rates experienced by patients, the appropriate method is to use the Fisherface algorithm method. This algorithm is used because of its ability to extract important information in imaging burn patterns on the body through the calculation of the average vector matrix and the covariance matrix in the pattern imaging database. In the process, the fisherface algorithm will generate an eigenface which is used for pattern recognition. Eigenface is the basis for calculating the points of burn patterns on the body which represent the individual values that represent one or more pattern images on the burns of the body. So, using Fisherface and Eigenface, it will be able to detect the body computerized during the process to determine the level of burns experienced by the patient.

Published in: 11th Annual International Conference on Industrial Engineering and Operations Management, Singapore, Singapore

Publisher: IEOM Society International
Date of Conference: March 7-11, 2021

ISBN: 978-1-7923-6124-1
ISSN/E-ISSN: 2169-8767