AIMC Topic: Burns
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Convolution neural network for effective burn region segmentation of color images.
Burns : journal of the International Society for Burn Injuries
Sep 12, 2020
BACKGROUND: Burn injuries are one of the most severe forms of wounds and trauma across the globe. Automated burn diagnosis methods are needed to provide timely treatment to the concerned patients. Artificial intelligence is playing a vital role in de...
Novel application of an automated-machine learning development tool for predicting burn sepsis: proof of concept.
Scientific reports
Jul 23, 2020
Sepsis is the primary cause of burn-related mortality and morbidity. Traditional indicators of sepsis exhibit poor performance when used in this unique population due to their underlying hypermetabolic and inflammatory response following burn injury....
Effectiveness of robot-assisted gait training on patients with burns: a preliminary study.
Computer methods in biomechanics and biomedical engineering
May 29, 2020
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
May 4, 2020
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...
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
Feb 11, 2020
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.
Early Recognition of Burn- and Trauma-Related Acute Kidney Injury: A Pilot Comparison of Machine Learning Techniques.
Scientific reports
Jan 14, 2020
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 ...
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
Jun 21, 2019
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 ...
Refractory collapse and severe burn: Think about acute adrenal insufficiency.
The American journal of emergency medicine
Dec 29, 2017
INTRODUCTION: Adrenal insufficiency (AI) is a rare endocrine disorder, which can in its acute form be life-threatening in case of late diagnosis or treatment. The stress during a thermal burn can easily decompensate the AI. We report the case of an a...
Effect of nano-silver, nano-copper, deconex and benzalkonium chloride on biofilm formation and expression of transcription regulatory quorum sensing gene (rh1R) in drug-resistance Pseudomonas aeruginosa burn isolates.
Burns : journal of the International Society for Burn Injuries
Dec 28, 2017
BACKGROUND: Biofilm forming drug-resistant Pseudomonas aeruginosa are responsible for major death in burn center of different hospitals across the globe.
Seeing the forest beyond the trees: Predicting survival in burn patients with machine learning.
American journal of surgery
Nov 7, 2017
BACKGROUND: This study aims to identify predictors of survival for burn patients at the patient and hospital level using machine learning techniques.
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