Esophageal Stricture as a Complication After Scald Injury in Children

Boscarelli, Alessandro; Fiorenza, Venusia; Chiaro, Andrea; Incerti, Filippo; Mattioli, Girolamo; Gandullia, Paolo

doi:10.1093/jbcr/iraa027

Cited by 2 publications

(1 citation statement)

References 4 publications

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“…Contusions are also sustained accidentally in toddlers due to tumbling plays during their early exploration pursuit. Similar reports related burn injuries have indicated its prominence in children [19,20]. Those contusions occurring at bony prominences such as knees, elbows, anterior tibiae and forehead are mostly due to accidental causes [21].…”

Section: Pressure Ulcer and Bruisesmentioning

confidence: 70%

Comparison of Deep Transfer Learning Techniques in Human Skin Burns Discrimination

Abubakar

Ajuji

Yahya

2020

ASI

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While visual assessment is the standard technique for burn evaluation, computer-aided diagnosis is increasingly sought due to high number of incidences globally. Patients are increasingly facing challenges which are not limited to shortage of experienced clinicians, lack of accessibility to healthcare facilities and high diagnostic cost. Certain number of studies were proposed in discriminating burn and healthy skin using machine learning leaving a huge and important gap unaddressed; whether burns and related skin injuries can be effectively discriminated using machine learning techniques. Therefore, we specifically use transfer learning by leveraging pre-trained deep learning models due to deficient dataset in this paper, to discriminate two classes of skin injuries—burnt skin and injured skin. Experiments were extensively conducted using three state-of-the-art pre-trained deep learning models that includes ResNet50, ResNet101 and ResNet152 for image patterns extraction via two transfer learning strategies—fine-tuning approach where dense and classification layers were modified and trained with features extracted by base layers and in the second approach support vector machine (SVM) was used to replace top-layers of the pre-trained models, trained using off-the-shelf features from the base layers. Our proposed approach records near perfect classification accuracy in categorizing burnt skin ad injured skin of approximately 99.9%.

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Section: Pressure Ulcer and Bruisesmentioning

confidence: 70%

Comparison of Deep Transfer Learning Techniques in Human Skin Burns Discrimination

Abubakar

Ajuji

Yahya

2020

ASI

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Predictive Importance of Lifestyle Improvement After Endoscopic Mucosal Resection for Esophageal Stricture in Superficial Esophageal Cancer and Precancerous Lesions: A Multi-Center Propensity Score Matching Study

Cui,

Chen,

Luo

et al. 2024

Preprint

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Background Esophageal stricture is a common complication following endoscopic submucosal dissection (ESD). This study aims to examine additional lifestyle factors contributing to post-ESD esophageal stricture and to propose guidelines for postoperative lifestyle management. Methods The least absolute shrinkage and selection operator (LASSO) logistic regression was employed to identify risk factors and construct nomograms, utilizing external 5-fold cross-validation to validate the results. Additionally, the Shapley additive explanations (SHAP) model was used for visualization. Results The identified risk factors for esophageal stricture include: operative duration (P = 0.008, OR = 1.837, 95% CI: 1.421–10.652), thickening of the esophageal wall (P = 0.027, OR = 3.448, 95% CI: 1.148–10.576), circumferential range (P < 0.001, OR = 6.026, 95% CI: 2.187–18.425), depth of infiltration (P < 0.001, OR = 4.940, 95% CI: 1.893–13.371), neutrophil-to-lymphocyte ratio (NLR) (P = 0.003, OR = 5.010, 95% CI: 1.755–15.156), intake of high-temperature food after surgery (P = 0.014, OR = 3.600, 95% CI: 1.314–10.261), and swallowing training (P = 0.047, OR = 3.140, 95% CI: 1.035–10.134). The area under the curve (AUC) for the training set of the predictive model is 0.924, while the AUC for the validation set is 0.904, and for the test set, it is 0.873. Conclusion reducing the intake of hot foods and engaging in swallowing training for a minimum of 3–6 months, can significantly reduce the incidence of esophageal stricture.

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Esophageal Stricture as a Complication After Scald Injury in Children

Cited by 2 publications

References 4 publications

Comparison of Deep Transfer Learning Techniques in Human Skin Burns Discrimination

Comparison of Deep Transfer Learning Techniques in Human Skin Burns Discrimination

Predictive Importance of Lifestyle Improvement After Endoscopic Mucosal Resection for Esophageal Stricture in Superficial Esophageal Cancer and Precancerous Lesions: A Multi-Center Propensity Score Matching Study

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