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Burns

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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 ...

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...

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...

[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...

[Advances in the research of application of artificial intelligence in burn field].

Zhonghua shao shang za zhi = Zhonghua shaoshang zazhi = Chinese journal of burns
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,...

[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
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...

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
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...

Big Data and Machine Learning in Plastic Surgery: A New Frontier in Surgical Innovation.

Plastic and reconstructive surgery
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 ...