AI Medical Compendium Topic:
Postoperative Complications

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Robot-Assisted Minimally Invasive Esophagectomy with Intrathoracic Anastomosis (Ivor Lewis): Promising Results in 100 Consecutive Patients (the European Experience).

Journal of gastrointestinal surgery : official journal of the Society for Surgery of the Alimentary Tract
BACKGROUND: Robot-assisted minimally invasive esophagectomy (RAMIE) with intrathoracic anastomosis is gaining popularity as a treatment for esophageal cancer. The aim of this study was to describe postoperative complications and short-term oncologic ...

Machine Learning for Predicting Complications in Head and Neck Microvascular Free Tissue Transfer.

The Laryngoscope
OBJECTIVES/HYPOTHESIS: Machine learning (ML) is a type of artificial intelligence wherein a computer learns patterns and associations between variables to correctly predict outcomes. The objectives of this study were to 1) use a ML platform to identi...

Development and validation of machine learning models to predict gastrointestinal leak and venous thromboembolism after weight loss surgery: an analysis of the MBSAQIP database.

Surgical endoscopy
BACKGROUND: Postoperative gastrointestinal leak and venous thromboembolism (VTE) are devastating complications of bariatric surgery. The performance of currently available predictive models for these complications remains wanting, while machine learn...

Preliminary experience with an image-free handheld robot for total knee arthroplasty: 77 cases compared with a matched control group.

European journal of orthopaedic surgery & traumatology : orthopedie traumatologie
BACKGROUND: Achieving an optimal limb alignment is an important factor affecting the long-term survival of total knee arthroplasty (TKA). This is the first study to look at the limb alignment and orientation of components in TKA using a novel image-f...

Perioperative adverse events in women over age 65 undergoing robot-assisted sacrocolpopexy.

International urogynecology journal
INTRODUCTION AND HYPOTHESIS: Pelvic floor disorders are common among and disproportionately affect older women. There are limited data regarding perioperative adverse events in older women undergoing robot-assisted sacrocolpopexy (RASC) specifically....

Artificial intelligence, machine learning and the pediatric airway.

Paediatric anaesthesia
Artificial intelligence and machine learning are rapidly expanding fields with increasing relevance in anesthesia and, in particular, airway management. The ability of artificial intelligence and machine learning algorithms to recognize patterns from...

Machine learning methods are comparable to logistic regression techniques in predicting severe walking limitation following total knee arthroplasty.

Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA
PURPOSE: Machine-learning methods are flexible prediction algorithms with potential advantages over conventional regression. This study aimed to use machine learning methods to predict post-total knee arthroplasty (TKA) walking limitation, and to com...

Machine learning of physiological waveforms and electronic health record data to predict, diagnose and treat haemodynamic instability in surgical patients: protocol for a retrospective study.

BMJ open
INTRODUCTION: About 42 million surgeries are performed annually in the USA. While the postoperative mortality is less than 2%, 12% of all patients in the high-risk surgery group account for 80% of postoperative deaths. New onset of haemodynamic insta...

Machine learning for the prediction of acute kidney injury and paraplegia after thoracoabdominal aortic aneurysm repair.

Journal of cardiac surgery
OBJECTIVE: Prediction of acute renal failure (ARF) and paraplegia after thoracoabdominal aortic aneurysm repair (TAAAR) is helpful for decision-making during the postoperative phase. To find a more efficient method for making a prediction, we perform...