Prediction of burn healing time using artificial neural networks and reflectance spectrometer
Resource
BURNS v.31 n.4 pp.415-420
Journal
BURNS
Journal Volume
v.31
Journal Issue
n.4
Pages
415-420
Date Issued
2005
Date
2005
Author(s)
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: Burns 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:Forty-one 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 etermine the burn healing time with 86% overall predictive accuracy.
Subjects
Burn healing time
Artificial neural network
Reflectance spectrometer
SDGs
Other Subjects
accuracy; article; artificial neural network; burn; clinical article; controlled study; disease severity; healing; human; prediction; reflectometry; Adolescent; Adult; Aged; Burns; Child; Data Interpretation, Statistical; Female; Humans; Male; Middle Aged; Neural Networks (Computer); Predictive Value of Tests; Scattering, Radiation; Spectrophotometry; Wound Healing
Type
journal article
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