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Neural Network Model to Detect Long-Term Skin and Soft Tissue Infection after Hernia Repair
Surgical Infections ( IF 2 ) Pub Date : 2021-08-05 , DOI: 10.1089/sur.2020.354
William J O'Brien 1, 2 , Radwan Dipp Ramos 1 , Kalpana Gupta 1, 3 , Kamal M F Itani 1, 3, 4
Affiliation  

Background: Skin and soft tissue infection (SSTI) after hernia surgery is infrequent yet catastrophic and is associated with mesh infection, interventions, and hernia recurrence. Although hernia repair is one of the most common general surgery procedures, uncertainty persists regarding incidence of long-term infections. Our goal is to develop a machine learning regression model that detects the occurrence of long-term hernia-associated SSTI.

中文翻译:

用于检测疝修补术后长期皮肤和软组织感染的神经网络模型

背景:疝气手术后的皮肤和软组织感染 (SSTI) 不常见但具有灾难性,并且与补片感染、干预和疝气复发有关。尽管疝气修复是最常见的普通外科手术之一,但长期感染的发生率仍存在不确定性。我们的目标是开发一个机器学习回归模型来检测长期疝气相关 SSTI 的发生。
更新日期:2021-09-02
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