DocumentCode :
2878323
Title :
Prediction of burn healing time using artificial neural networks and reflectance spectrometer
Author :
Yeong, Eng-kean ; Hsiao, Tzu-Chien ; Chiang, Huihua Kenny ; Lin, Chii-Wann
Author_Institution :
Dept. of Surg., Nat. Taiwan Univ., Taipei, Taiwan
fYear :
2004
fDate :
14-17 Dec. 2004
Firstpage :
143
Abstract :
Burn depth assessment is important as early excision and grafting is the treatment of choice for deep dermal burn. Inaccurate assessment causes prolonged hospital stay, increased medical expenses and morbidity. Based on reflected burn spectra, we have developed an artificial neural network to predict the burn healing time. The purpose of our study is to develop a noninvasive objective method to predict burn-healing time. Burn less than 20% TBSA was included. Burn spectra taken on the third postburn day using reflectance spectrometer were analyzed by an artificial neural network system. 41 spectra were collected. With the newly developed method, the predictive accuracy of burns healed in less than 14 days was 96% and that in more than 14 days was 75%. Using reflectance spectrometer, we have developed an artificial neural network to determine the burn healing time with 86% overall predictive accuracy.
Keywords :
bio-optics; neural nets; reflectivity; spectrometers; artificial neural network; burn depth assessment; burn healing time prediction; reflectance spectrometer; reflected burn spectra; Accuracy; Artificial neural networks; Biomedical engineering; Dermis; Educational institutions; Hospitals; Plastics; Reflectivity; Spectroscopy; Surgery;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Biophotonics, 2004. APBP 2004. The Second Asian and Pacific Rim Symposium on
Print_ISBN :
0-7803-8676-0
Type :
conf
DOI :
10.1109/APBP.2004.1412321
Filename :
1412321
Link To Document :
بازگشت