BACKGROUND: Many machine learning (ML) algorithms have been used to develop surgical site infection (SSI) prediction models, but little is known about their predicting performance. We conducted a network meta-analysis to compare the performance of di...
This retrospective study leverages machine learning to determine the optimal timing for fracture reconstruction surgery in polytrauma patients, focusing on those with concomitant traumatic brain injury. The analysis included 218 patients admitted to ...
The Journal of international medical research
Nov 1, 2024
OBJECTIVE: To externally validate by revision and update the study on the efficacy of nosocomial infection control (SENIC) model of surgical site infection (SSI) using logistic regression (LR) and machine learning (ML) approaches.
OBJECTIVES: Robot-assisted laparoscopic surgeries (RLSs) have become increasingly common in the past decade alongside conventional laparoscopic surgeries (CLSs). In general, RLSs have been reported to be superior to CLSs; therefore, we compared both ...
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Nov 1, 2021
The ability to detect surgical site infections (SSI) is a critical need for healthcare worldwide, but is especially important in low-income countries, where there is limited access to health facilities and trained clinical staff. In this paper, we pr...
<b>Introduction:</b> The effect of BMI on development of perioperative complications in head and neck cancer surgeries is not welldefined. </br></br> <b> Aim:</b> This study aims to evaluate the effect of body mass...
Beijing da xue xue bao. Yi xue ban = Journal of Peking University. Health sciences
Dec 30, 2020
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.
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