AIMC Topic: Burns

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Time-Independent Prediction of Burn Depth Using Deep Convolutional Neural Networks.

Journal of burn care & research : official publication of the American Burn Association Oct 16, 2019
We present in this paper the application of deep convolutional neural networks (CNNs), which is a state-of-the-art artificial intelligence (AI) approach in machine learning, for automated time-independent prediction of burn depth. Color images of fou...
Image Processing, Computer-Assisted Skin Burns Photography Humans Neural Networks, Computer Sensitivity and Specificity
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Burn wound classification model using spatial frequency-domain imaging and machine learning.

Journal of biomedical optics May 1, 2019
Accurate assessment of burn severity is critical for wound care and the course of treatment. Delays in classification translate to delays in burn management, increasing the risk of scarring and infection. To this end, numerous imaging techniques have...
Light Calibration Optical Imaging Optics and Photonics Color Skin Burns Reproducibility of Results Sensitivity and Specificity Animals Machine Learning Support Vector Machine Swine Software Wound Healing Severity of Illness Index Algorithms
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Predicting the Ability of Wounds to Heal Given Any Burn Size and Fluid Volume: An Analytical Approach.

Journal of burn care & research : official publication of the American Burn Association Aug 17, 2018
The intrinsic relationship between fluid volume and open wound size (%) has not been previously examined. Therefore, we conducted this study to investigate whether open wound size can be predicted from fluid volume plus other significant factors over...
Machine Learning Retrospective Studies Female Reproducibility of Results Humans Middle Aged Age Factors Wound Healing Predictive Value of Tests Hospitalization Adult Male Crystalloid Solutions Fluid Therapy Burns Multivariate Analysis
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[Comparison of machine learning method and logistic regression model in prediction of acute kidney injury in severely burned patients].

Zhonghua shao shang za zhi = Zhonghua shaoshang zazhi = Chinese journal of burns Jun 20, 2018
To build risk prediction models for acute kidney injury (AKI) in severely burned patients, and to compare the prediction performance of machine learning method and logistic regression model. The clinical data of 157 severely burned patients in Augu...
Organ Dysfunction Scores Explosions Hospitalization Sensitivity and Specificity Sepsis Humans Fluid Therapy Machine Learning Burns Acute Kidney Injury ROC Curve Logistic Models
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[Advances in the research of application of artificial intelligence in burn field].

Zhonghua shao shang za zhi = Zhonghua shaoshang zazhi = Chinese journal of burns Apr 20, 2018
Artificial intelligence has been able to automatically learn and judge large-scale data to some extent. Based on database of a large amount of burn data and in-depth learning, artificial intelligence can assist burn surgeons to evaluate burn surface,...
Prognosis Burns Shock Humans Artificial Intelligence
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[Changes of platelet rheological behavior and the interventional effects of ulinastatin in rats with high-voltage electrical burns].

Zhonghua shao shang za zhi = Zhonghua shaoshang zazhi = Chinese journal of burns Dec 20, 2017
To explore the influence of high-voltage electrical burns on the number of platelet aggregation, β-thromboglobulin (β-TG) and platelet factor 4 (PF-4) and the interventional effects of ulinastatin in rats with high-voltage electrical burns. A total...
Rats, Sprague-Dawley Burns Glycoproteins Blood Platelets Animals Serum Platelet Aggregation beta-Thromboglobulin Burns, Electric Rats Trypsin Inhibitors Microcirculation Enzyme-Linked Immunosorbent Assay
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Non-invasive optical imaging techniques for burn-injured tissue detection for debridement surgery.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Aug 1, 2016
Burn debridement is a challenging technique that requires significant skill to identify regions requiring excision and appropriate excision depth. A machine learning tool is being developed in order to assist surgeons by providing a quantitative asse...
Skin Burns Surgery, Computer-Assisted Debridement Dermatologic Surgical Procedures Animals Optical Imaging Swine Disease Models, Animal
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Big Data and Machine Learning in Plastic Surgery: A New Frontier in Surgical Innovation.

Plastic and reconstructive surgery May 1, 2016
Medical decision-making is increasingly based on quantifiable data. From the moment patients come into contact with the health care system, their entire medical history is recorded electronically. Whether a patient is in the operating room or on the ...
Machine Learning Clinical Decision-Making Humans Motor Skills Plastic Surgery Procedures Clinical Competence Hand Peripheral Nerves Burns Datasets as Topic Microsurgery Surgery, Plastic Internship and Residency Craniosynostoses Teaching
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Outlier detection and removal improves accuracy of machine learning approach to multispectral burn diagnostic imaging.

Journal of biomedical optics Dec 1, 2015
Multispectral imaging (MSI) was implemented to develop a burn tissue classification device to assist burn surgeons in planning and performing debridement surgery. To build a classification model via machine learning, training data accurately represen...
Pattern Recognition, Automated Image Enhancement Optical Imaging Subtraction Technique Burns Image Interpretation, Computer-Assisted Artifacts Spectrum Analysis Animals Swine Algorithms Skin Machine Learning Dermoscopy Reproducibility of Results Sensitivity and Specificity
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