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Burns

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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
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...

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
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...

Burn wound classification model using spatial frequency-domain imaging and machine learning.

Journal of biomedical optics
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...

Artificial intelligence and machine learning for predicting acute kidney injury in severely burned patients: A proof of concept.

Burns : journal of the International Society for Burn Injuries
BACKGROUND: Burn critical care represents a high impact population that may benefit from artificial intelligence and machine learning (ML). Acute kidney injury (AKI) recognition in burn patients could be enhanced by ML. The goal of this study was to ...

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

Journal of burn care & research : official publication of the American Burn Association
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...

Early Recognition of Burn- and Trauma-Related Acute Kidney Injury: A Pilot Comparison of Machine Learning Techniques.

Scientific reports
Severely burned and non-burned trauma patients are at risk for acute kidney injury (AKI). The study objective was to assess the theoretical performance of artificial intelligence (AI)/machine learning (ML) algorithms to augment AKI recognition using ...

Effects of interactive robot-enhanced hand rehabilitation in treatment of paediatric hand-burns: A randomized, controlled trial with 3-months follow-up.

Burns : journal of the International Society for Burn Injuries
PURPOSE: To evaluate the effectiveness of the robotic-assisted exercise with virtual gaming on total active range of motion (ROM) of the digits, hand grip strength (HGS), and hand function in children with hand burns.

[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
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...

Effectiveness of robot-assisted gait training on patients with burns: a preliminary study.

Computer methods in biomechanics and biomedical engineering
Gait enables individuals to move forward and is considered a natural skill. However, gait disturbances are very common in patients with burn injury. Recent studies have emphasized the role of robot-assisted gait training (RAGT) in rehabilitation. Thi...

BPBSAM: Body part-specific burn severity assessment model.

Burns : journal of the International Society for Burn Injuries
BACKGROUND AND OBJECTIVE: Burns are a serious health problem leading to several thousand deaths annually, and despite the growth of science and technology, automated burns diagnosis still remains a major challenge. Researchers have been exploring vis...