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

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

doi:10.1109/APBP.2004.1412321

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

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

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

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.

Original language	English
Title of host publication	Second Asian and Pacific Rim Symposium on Biophotonics - Proceedings, APBP 2004
Pages	143
Number of pages	1
DOIs	https://doi.org/10.1109/APBP.2004.1412321
State	Published - 2004
Event	Second Asian and Pacific Rim Symposium on Biophotonics, APBP 2004 - Taipei, Taiwan Duration: 15 Dec 2004 → 17 Dec 2004

Publication series

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

Conference

Conference	Second Asian and Pacific Rim Symposium on Biophotonics, APBP 2004
Country/Territory	Taiwan
City	Taipei
Period	15/12/04 → 17/12/04

Access to Document

10.1109/APBP.2004.1412321

Cite this

Yeong, E. K., Hsiao, T. C., Chiang, H. K., & Lin, C. W. (2004). Prediction of burn healing time using artificial neural networks and reflectance spectrometer. In Second Asian and Pacific Rim Symposium on Biophotonics - Proceedings, APBP 2004 (pp. 143). (Second Asian and Pacific Rim Symposium on Biophotonics - Proceedings, APBP 2004). https://doi.org/10.1109/APBP.2004.1412321

@inproceedings{01347a0fe33a458ab383059cbe348638,

title = "Prediction of burn healing time using artificial neural networks and reflectance spectrometer",

abstract = "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.",

author = "Yeong, {Eng Kean} and Hsiao, {Tzu Chien} and Chiang, {Huihua Kenny} and Lin, {Chii Wann}",

year = "2004",

doi = "10.1109/APBP.2004.1412321",

language = "English",

isbn = "0780386760",

series = "Second Asian and Pacific Rim Symposium on Biophotonics - Proceedings, APBP 2004",

pages = "143",

booktitle = "Second Asian and Pacific Rim Symposium on Biophotonics - Proceedings, APBP 2004",

note = "Second Asian and Pacific Rim Symposium on Biophotonics, APBP 2004 ; Conference date: 15-12-2004 Through 17-12-2004",

}

Yeong, EK, Hsiao, TC , Chiang, HK & Lin, CW 2004, Prediction of burn healing time using artificial neural networks and reflectance spectrometer. in Second Asian and Pacific Rim Symposium on Biophotonics - Proceedings, APBP 2004. Second Asian and Pacific Rim Symposium on Biophotonics - Proceedings, APBP 2004, pp. 143, Second Asian and Pacific Rim Symposium on Biophotonics, APBP 2004, Taipei, Taiwan, 15/12/04. https://doi.org/10.1109/APBP.2004.1412321

Prediction of burn healing time using artificial neural networks and reflectance spectrometer. / Yeong, Eng Kean; Hsiao, Tzu Chien ; Chiang, Huihua Kenny et al.
Second Asian and Pacific Rim Symposium on Biophotonics - Proceedings, APBP 2004. 2004. p. 143 (Second Asian and Pacific Rim Symposium on Biophotonics - Proceedings, APBP 2004).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Prediction of burn healing time using artificial neural networks and reflectance spectrometer

AU - Yeong, Eng Kean

AU - Hsiao, Tzu Chien

AU - Chiang, Huihua Kenny

AU - Lin, Chii Wann

PY - 2004

Y1 - 2004

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=20844432061&partnerID=8YFLogxK

U2 - 10.1109/APBP.2004.1412321

DO - 10.1109/APBP.2004.1412321

M3 - Conference contribution

AN - SCOPUS:20844432061

SN - 0780386760

T3 - Second Asian and Pacific Rim Symposium on Biophotonics - Proceedings, APBP 2004

SP - 143

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

T2 - Second Asian and Pacific Rim Symposium on Biophotonics, APBP 2004

Y2 - 15 December 2004 through 17 December 2004

ER -

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

Abstract

Publication series

Conference

Access to Document

Other files and links

Fingerprint

Cite this