AIMC Topic: Burns

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Autonomous Multi-modality Burn Wound Characterization using Artificial Intelligence.

Military medicine Nov 8, 2023
INTRODUCTION: Between 5% and 20% of all combat-related casualties are attributed to burn wounds. A decrease in the mortality rate of burns by about 36% can be achieved with early treatment, but this is contingent upon accurate characterization of the...
Animals Swine Ultrasonography Burns Humans Artificial Intelligence
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Clinical Investigation of a Rapid Non-invasive Multispectral Imaging Device Utilizing an Artificial Intelligence Algorithm for Improved Burn Assessment.

Journal of burn care & research : official publication of the American Burn Association Jul 5, 2023
Currently, the incorrect judgment of burn depth remains common even among experienced surgeons. Contributing to this problem are change in burn appearance throughout the first week requiring periodic evaluation until a confident diagnosis can be made...
Algorithms Wound Healing Skin Humans Neural Networks, Computer Artificial Intelligence Burns
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[Research advances on functional training robots in burn rehabilitation].

Zhonghua shao shang yu chuang mian xiu fu za zhi Jun 20, 2022
Patients with deep burns are prone to suffer cicatrix hyperplasia or contracture, leading to problems including dysfunction in limbs, which impacts patients' life quality and makes it difficult for them to return to society. Thereby, the rehabilitati...
Humans Robotics Exercise Therapy Cicatrix Contracture Burns
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Potential for Machine Learning in Burn Care.

Journal of burn care & research : official publication of the American Burn Association May 17, 2022
Burn-related injuries are a leading cause of morbidity across the globe. Accurate assessment and treatment have been demonstrated to reduce the morbidity and mortality. This essay explores the forms of artificial intelligence to be implemented the fi...
State Medicine Machine Learning Logistic Models Burns Humans Artificial Intelligence
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Enhancing Military Burn- and Trauma-Related Acute Kidney Injury Prediction Through an Automated Machine Learning Platform and Point-of-Care Testing.

Archives of pathology & laboratory medicine Mar 1, 2021
CONTEXT.—: Delayed recognition of acute kidney injury (AKI) results in poor outcomes in military and civilian burn-trauma care. Poor predictive ability of urine output (UOP) and creatinine contribute to the delayed recognition of AKI.
Wounds and Injuries Humans Machine Learning Lipocalin-2 Algorithms Acute Kidney Injury Burns Biomarkers Female Creatinine Middle Aged Aged Military Personnel Predictive Value of Tests Point-of-Care Testing Aged, 80 and over Adult Male
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[Advances in the research of artificial intelligence technology assisting the diagnosis of burn depth].

Zhonghua shao shang za zhi = Zhonghua shaoshang zazhi = Chinese journal of burns Mar 20, 2020
The early accurate diagnosis of burn depth is of great significance in determining the corresponding clinical intervention methods and judging the prognosis quality of burn patients. However, the current diagnostic method of burn depth still relies m...
Burns Technology Early Diagnosis Humans Prognosis Artificial Intelligence Skin
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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...
Photography Humans Neural Networks, Computer Skin Burns Sensitivity and Specificity Image Processing, Computer-Assisted
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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...
Reproducibility of Results Sensitivity and Specificity Animals Support Vector Machine Wound Healing Swine Severity of Illness Index Machine Learning Software Algorithms Optics and Photonics Light Calibration Optical Imaging Color Skin Burns
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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...
Burns Multivariate Analysis Crystalloid Solutions Female Reproducibility of Results Hospitalization Humans Machine Learning Retrospective Studies Age Factors Wound Healing Predictive Value of Tests Fluid Therapy Adult Male Middle Aged
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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...
ROC Curve Logistic Models Fluid Therapy Hospitalization Burns Organ Dysfunction Scores Explosions Humans Machine Learning Acute Kidney Injury Sensitivity and Specificity Sepsis
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