AI Medical Compendium Journal:
BMC surgery

Showing 1 to 10 of 43 articles

Assessing artificial intelligence ability in predicting hospitalization duration for pleural empyema patients managed with uniportal video-assisted thoracoscopic surgery: a retrospective observational study.

BMC surgery
BACKGROUND: This retrospective observational research evaluates the potential applicability of artificial intelligence models to predict the length of hospital stay for patients with pleural empyema who underwent uniportal video-assisted thoracoscopi...

Machine learning-based prediction of postoperative pancreatic fistula after laparoscopic pancreaticoduodenectomy.

BMC surgery
BACKGROUND: Clinically relevant postoperative pancreatic fistula (CR-POPF) following laparoscopic pancreaticoduodenectomy (LPD) is a critical complication that significantly worsens patient outcomes. However, the heterogeneity of its risk factors and...

Diagnostic accuracy of artificial intelligence algorithms to predict remove all macroscopic disease and survival rate after complete surgical cytoreduction in patients with ovarian cancer: a systematic review and meta-analysis.

BMC surgery
BACKGROUND: Complete Cytoreduction (CC) in ovarian cancer (OC) has been associated with better outcomes. Outcomes after CC have a multifactorial and interrelated cause that may not be predictable by conventional statistical methods. Artificial intell...

Development of a LASSO machine learning algorithm-based model for postoperative delirium prediction in hepatectomy patients.

BMC surgery
OBJECTIVE: The objective of this study was to develop and validate a clinically applicable nomogram for predicting the risk of delirium following hepatectomy.

Revolutionizing spinal interventions: a systematic review of artificial intelligence technology applications in contemporary surgery.

BMC surgery
Leveraging its ability to handle large and complex datasets, artificial intelligence can uncover subtle patterns and correlations that human observation may overlook. This is particularly valuable for understanding the intricate dynamics of spinal su...

Machine learning-based prediction models affecting the recovery of postoperative bowel function for patients undergoing colorectal surgeries.

BMC surgery
PURPOSE: The debate surrounding factors influencing postoperative flatus and defecation in patients undergoing colorectal resection prompted this study. Our objective was to identify independent risk factors and develop prediction models for postoper...

Predicting osteoporotic fractures post-vertebroplasty: a machine learning approach with a web-based calculator.

BMC surgery
PURPOSE: The aim of this study was to develop and validate a machine learning (ML) model for predicting the risk of new osteoporotic vertebral compression fracture (OVCF) in patients who underwent percutaneous vertebroplasty (PVP) and to create a use...

Single-port robotic-assisted laparoscopic synchronous surgery in pediatric patent processus vaginalis.

BMC surgery
PURPOSE: Patent processus vaginalis (PPV) is usually observed in pediatric abdominal surgery; however, robotic single-port surgery in repairing processus vaginalis has not been reported in children. Herein, we present our clinical experiences in sing...

Gasless robot-assisted transaxillary hemithyroidectomy (RATH): learning curve and complications.

BMC surgery
PURPOSE: Gasless robot-assisted transaxillary hemithyroidectomy (RATH) is regarded as an alternative surgical option for thyroid operations. However, the associated steep learning curve is a clinical concern. This study evaluated the learning curve o...