AIMC Topic: Postoperative Complications

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Assessing the perioperative outcomes of abdominal drain omission after robot-assisted partial nephrectomy.

Scientific reports Apr 15, 2024
The study aimed to evaluate the impact of abdominal drain placement (vs. omission) on perioperative outcomes of robot-assisted partial nephrectomy (RAPN), focusing on complications, time to canalization, deambulation, and pain management. A prospecti...
Robotics Kidney Neoplasms Nephrectomy Postoperative Complications Kidney Treatment Outcome Humans Retrospective Studies
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Machine learning for enhanced prognostication: predicting 30-day outcomes following posterior fossa decompression surgery for Chiari malformation type I in a pediatric cohort.

Journal of neurosurgery. Pediatrics Apr 12, 2024
OBJECTIVE: Chiari malformation type I (CM-I) is a congenital disorder occurring in 0.1% of the population. In symptomatic cases, surgery with posterior fossa decompression (PFD) is the treatment of choice. Surgery is, however, associated with peri- a...
Machine Learning Prognosis Retrospective Studies Postoperative Complications Adolescent Female Male Humans Arnold-Chiari Malformation Cranial Fossa, Posterior Treatment Outcome Patient Readmission Reoperation Decompression, Surgical Cohort Studies Child, Preschool Child
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Supervised machine learning for the prediction of post-operative clinical outcomes of hip and knee replacements: a review.

ANZ journal of surgery Apr 10, 2024
Prediction models are being increasingly used in the medical field to identify risk factors and possible outcomes. Some of these are presently being used to develop guidelines for improving clinical practice. The application of machine learning (ML),...
Arthroplasty, Replacement, Knee Arthroplasty, Replacement, Hip Humans Treatment Outcome Supervised Machine Learning Machine Learning Postoperative Complications
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Development and validation of machine learning models to predict postoperative infarction in moyamoya disease.

Journal of neurosurgery Apr 5, 2024
OBJECTIVE: Cerebral infarction is a common complication in patients undergoing revascularization surgery for moyamoya disease (MMD). Although previous statistical evaluations have identified several risk factors for postoperative brain ischemia, the ...
Cerebral Infarction Moyamoya Disease Cerebral Revascularization Young Adult Adult Male Support Vector Machine Machine Learning Predictive Value of Tests Retrospective Studies Middle Aged Humans Female Postoperative Complications
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Precise highlighting of the pancreas by semantic segmentation during robot-assisted gastrectomy: visual assistance with artificial intelligence for surgeons.

Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association Apr 4, 2024
BACKGROUND: A postoperative pancreatic fistula (POPF) is a critical complication of radical gastrectomy for gastric cancer, mainly because surgeons occasionally misrecognize the pancreas and fat during lymphadenectomy. Therefore, this study aimed to ...
Humans Artificial Intelligence Algorithms Stomach Neoplasms Gastrectomy Pancreas Pancreatic Fistula Surgeons Postoperative Complications Robotic Surgical Procedures
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Reply to: Letter to Editor Regarding Article "A Machine Learning Approach to Predict Postoperative Pancreatic Fistula after Pancreaticoduodenectomy Using Only Preoperatively Known Data" by Yang, Yanfei et al.

Annals of surgical oncology Apr 3, 2024
Humans Machine Learning Pancreatic Neoplasms Prognosis Pancreatic Fistula Postoperative Complications Pancreaticoduodenectomy
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Letter to Editor Regarding Article "A Machine Learning Approach to Predict Postoperative Pancreatic Fistula After Pancreaticoduodenectomy Using Only Preoperatively Known Data".

Annals of surgical oncology Apr 1, 2024
Machine Learning Prognosis Postoperative Complications Pancreaticoduodenectomy Pancreatic Neoplasms Humans Pancreatic Fistula
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Machine learning prediction model of major adverse outcomes after pediatric congenital heart surgery: a retrospective cohort study.

International journal of surgery (London, England) Apr 1, 2024
BACKGROUND: Major adverse postoperative outcomes (APOs) can greatly affect mortality, hospital stay, care management and planning, and quality of life. This study aimed to evaluate the performance of five machine learning (ML) algorithms for predicti...
Infant, Newborn Male Risk Assessment ROC Curve Postoperative Complications Humans Machine Learning Pneumonia Retrospective Studies Infant Cardiac Surgical Procedures Female Child, Preschool Heart Defects, Congenital Child
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Deep learning-based quantification of total bleeding volume and its association with complications, disability, and death in patients with aneurysmal subarachnoid hemorrhage.

Journal of neurosurgery Mar 29, 2024
OBJECTIVE: The relationships between immediate bleeding severity, postoperative complications, and long-term functional outcomes in patients with aneurysmal subarachnoid hemorrhage (aSAH) remain uncertain. Here, the authors apply their recently devel...
Male Female Subarachnoid Hemorrhage Middle Aged Deep Learning Aged Postoperative Complications Humans Hydrocephalus Adult Retrospective Studies Tomography, X-Ray Computed
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Predicting early return to the operating room in early-onset scoliosis patients using machine learning techniques.

Spine deformity Mar 26, 2024
PURPOSE: Surgical treatment of early-onset scoliosis (EOS) is associated with high rates of complications, often requiring unplanned return to the operating room (UPROR). The aim of this study was to create and validate a machine learning model to pr...
Male Postoperative Complications Child, Preschool Child Machine Learning Humans Retrospective Studies Female Reoperation Operating Rooms Spinal Fusion Age of Onset Scoliosis
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