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Time-Independent Pr...
Time-Independent Prediction of Burn Depth using Deep Convolutional Neural Networks
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- Cirillo, Marco Domenico (författare)
- Linköpings universitet,Avdelningen för medicinsk teknik,Tekniska fakulteten
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- Mirdell, Robin, 1989- (författare)
- Linköpings universitet,Avdelningen för Kirurgi, Ortopedi och Onkologi,Medicinska fakulteten,Region Östergötland, Hand- och plastikkirurgiska kliniken US
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- Sjöberg, Folke, 1956- (författare)
- Linköpings universitet,Avdelningen för Kirurgi, Ortopedi och Onkologi,Medicinska fakulteten,Region Östergötland, Hand- och plastikkirurgiska kliniken US
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- Pham, Tuan, Professor, 1962- (författare)
- Linköpings universitet,Avdelningen för medicinsk teknik,Tekniska fakulteten,Pattern Recognition
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(creator_code:org_t)
- 2019-06-11
- 2019
- Engelska.
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Ingår i: Journal of Burn Care & Research. - : Oxford University Press. - 1559-047X .- 1559-0488. ; 40:6, s. 857-863
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http://liu.diva-port...
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https://urn.kb.se/re...
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https://doi.org/10.1...
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Abstract
Ämnesord
Stäng
- We present in this paper the application of deep convolutional neural networks, which are a state-of-the-art artificial intelligence (AI) approach in machine learning, for automated time-independent prediction of burn depth. Colour images of four types of burn depth injured in first few days, including normal skin and background, acquired by a TiVi camera were trained and tested with four pre-trained deep convolutional neural networks: VGG-16, GoogleNet, ResNet-50, and ResNet-101. In the end, the best 10-fold cross-validation results obtained from ResNet- 101 with an average, minimum, and maximum accuracy are 81.66%, 72.06% and 88.06%, respectively; and the average accuracy, sensitivity and specificity for the four different types of burn depth are 90.54%, 74.35% and 94.25%, respectively. The accuracy was compared to the clinical diagnosis obtained after the wound had healed. Hence, application of AI is very promising for prediction of burn depth and therefore can be a useful tool to help in guiding clinical decision and initial treatment of burn wounds.
Ämnesord
- MEDICIN OCH HÄLSOVETENSKAP -- Klinisk medicin -- Kirurgi (hsv//swe)
- MEDICAL AND HEALTH SCIENCES -- Clinical Medicine -- Surgery (hsv//eng)
- TEKNIK OCH TEKNOLOGIER -- Medicinteknik -- Medicinsk bildbehandling (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Medical Engineering -- Medical Image Processing (hsv//eng)
- MEDICIN OCH HÄLSOVETENSKAP -- Klinisk medicin -- Annan klinisk medicin (hsv//swe)
- MEDICAL AND HEALTH SCIENCES -- Clinical Medicine -- Other Clinical Medicine (hsv//eng)
Nyckelord
- Burn depth
- time-independent prediction
- deep convolutional neural network
- artificial intelligence
Publikations- och innehållstyp
- ref (ämneskategori)
- art (ämneskategori)
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