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Surgical Wound Infection

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[Risk factors for multiple debridements of the patients with deep incisional surgical site infection after spinal surgery].

Beijing da xue xue bao. Yi xue ban = Journal of Peking University. Health sciences
OBJECTIVE: To investigate the risk factors that contribute to multiple debridements in patients suffering from deep incisional surgical site infection after spinal surgery and advise medical personnel to pay special attention to these risk factors.

Using Natural Language Processing to improve EHR Structured Data-based Surgical Site Infection Surveillance.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Surgical Site Infection surveillance in healthcare systems is labor intensive and plagued by underreporting as current methodology relies heavily on manual chart review. The rapid adoption of electronic health records (EHRs) has the potential to allo...

[Usefulness of the CONUT Score for Predicting the Risk of Surgical Site Infections].

Gan to kagaku ryoho. Cancer & chemotherapy
BACKGROUND: Surgical site infections(SSIs)occur at a high frequency in patients after rectal cancer surgery and are readily aggravated. Therefore, prophylactic measures for infections based on the evaluation of the patient's perioperative risk are ve...

Using artificial intelligence (AI) to predict postoperative surgical site infection: A retrospective cohort of 4046 posterior spinal fusions.

Clinical neurology and neurosurgery
OBJECTIVES: Machine Learning and Artificial Intelligence (AI) are rapidly growing in capability and increasingly applied to model outcomes and complications within medicine. In spinal surgery, post-operative surgical site infections (SSIs) are a rare...

Artificial intelligence-based tools to control healthcare associated infections: A systematic review of the literature.

Journal of infection and public health
BACKGROUND: Healthcare-associated infections (HAIs) are the most frequent adverse events in healthcare and a global public health concern. Surveillance is the foundation for effective HAIs prevention and control. Manual surveillance is labor intensiv...

Accelerating Surgical Site Infection Abstraction With a Semi-automated Machine-learning Approach.

Annals of surgery
OBJECTIVE: To demonstrate that a semi-automated approach to health data abstraction provides significant efficiencies and high accuracy.

Machine Learning-Based Gynecologic Tumor Diagnosis and Its Postoperative Incisional Infection Influence Factor Analysis.

Journal of healthcare engineering
Various factors influencing postoperative incisional infection in gynecologic tumors were analyzed, and the value of quality nursing intervention was studied. In this study, 74 surgically treated gynecologic tumor patients were randomly selected from...

Applying Machine Learning Across Sites: External Validation of a Surgical Site Infection Detection Algorithm.

Journal of the American College of Surgeons
BACKGROUND: Surgical complications have tremendous consequences and costs. Complication detection is important for quality improvement, but traditional manual chart review is burdensome. Automated mechanisms are needed to make this more efficient. To...