Prediction of burn healing time using artificial neural networks and reflectance spectrometer

Eng Kean Yeong*, Tzu Chien Hsiao, Huihua Kenny Chiang, Chii Wann Lin

*此作品的通信作者

研究成果: Conference contribution同行評審

摘要

Background: 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. Purpose: Our study is to develop a non-invasive objective method to predict burn-healing time. Methods and materials: Bum 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. Results: 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 %. Conclusions: Using reflectance spectrometer, we have developed an artificial neural network to determine the burn healing time with 86 % overall predictive accuracy.

原文English
主出版物標題Second Asian and Pacific Rim Symposium on Biophotonics - Proceedings, APBP 2004
頁面143
頁數1
DOIs
出版狀態Published - 2004
事件Second Asian and Pacific Rim Symposium on Biophotonics, APBP 2004 - Taipei, 台灣
持續時間: 15 12月 200417 12月 2004

出版系列

名字Second Asian and Pacific Rim Symposium on Biophotonics - Proceedings, APBP 2004

Conference

ConferenceSecond Asian and Pacific Rim Symposium on Biophotonics, APBP 2004
國家/地區台灣
城市Taipei
期間15/12/0417/12/04

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