2nd Asia Pacific International Conference on Industrial Engineering and Operations Management

Development of Automatic Wound Healing Level Detection System based on Convolutional Neural Network

Michael Ethan, Winda Astuti & Sofyan Tan
Publisher: IEOM Society International
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Track: Artificial Intelligence
Abstract

Wound is an unpleasant experience caused by tissue damage. The wound healing level is subjective, where each individual has a different perspective the level wound healing response, sometimes difficult to determine only by visual eyes and can only be felt by the individual without being felt by others. Therefore, the wound healing level determined the treatment by medical personnel to the patient. This could lead to non-standard handling of patients in  medical treatment. The automatic stand- alone system for healing wound level detection based on wound image recognition is developed. The system determines patient wound level detector based on wound image recognition. The level of the wound is detected based on wound image procession technique and Convolution Neural Network (CNN). The system is working properly, since it resulting the training and testing accuracy of 67% and 55%, respectively.

Published in: 2nd Asia Pacific International Conference on Industrial Engineering and Operations Management, Surakarta, Indonesia

Publisher: IEOM Society International
Date of Conference: September 13-16, 2021

ISBN: 978-1-7923-6129-6
ISSN/E-ISSN: 2169-8767