AI Medical Compendium Journal:
Surgery

Showing 41 to 50 of 78 articles

Robot-assisted versus conventional laparoscopic adrenalectomy: Results from the EUROCRINE Surgical Registry.

Surgery
BACKGROUND: Adrenalectomy is routinely performed via the minimally invasive approach. Safety of adrenalectomy using the robot-assisted technique has been widely demonstrated by several series, but the literature is scarce regarding the comparison of ...

Executive summary of the artificial intelligence in surgery series.

Surgery
As opportunities for artificial intelligence to augment surgical care expand, the accompanying surge in published literature has generated both substantial enthusiasm and grave concern regarding the safety and efficacy of artificial intelligence in s...

The prediction of surgical complications using artificial intelligence in patients undergoing major abdominal surgery: A systematic review.

Surgery
BACKGROUND: Conventional statistics are based on a simple cause-and-effect principle. Postoperative complications, however, have a multifactorial and interrelated etiology. The application of artificial intelligence might be more accurate to predict ...

Road to automating robotic suturing skills assessment: Battling mislabeling of the ground truth.

Surgery
OBJECTIVE: To automate surgeon skills evaluation using robotic instrument kinematic data. Additionally, to implement an unsupervised mislabeling detection algorithm to identify potentially mislabeled samples that can be removed to improve model perfo...

Using the Super Learner algorithm to predict risk of 30-day readmission after bariatric surgery in the United States.

Surgery
BACKGROUND: Risk prediction models that estimate patient probabilities of adverse events are commonly deployed in bariatric surgery. The objective was to validate a machine learning (Super Learner) prediction model of 30-day readmission after bariatr...

A machine learning approach for the prediction of overall deceased donor organ yield.

Surgery
BACKGROUND: Optimizing organ yield (number of organs transplanted per donor) is a potentially modifiable way to increase the number of organs available for transplant. Models to predict the expected deceased donor organ yield have been developed base...

Natural language processing for the surveillance of postoperative venous thromboembolism.

Surgery
BACKGROUND: The objective of this study was to develop a portal natural language processing approach to aid in the identification of postoperative venous thromboembolism events from free-text clinical notes.

Machine learning for the prediction of pathologic pneumatosis intestinalis.

Surgery
BACKGROUND: The radiographic finding of pneumatosis intestinalis can indicate a spectrum of underlying processes ranging from a benign finding to a life-threatening condition. Although radiographic pneumatosis intestinalis is relatively common, there...

Development of an algorithm for intraoperative autofluorescence assessment of parathyroid glands in primary hyperparathyroidism using artificial intelligence.

Surgery
BACKGROUND: Previous work showed that normal and abnormal parathyroid glands exhibit different patterns of autofluorescence, with the former appearing brighter and more homogenous. However, an objective algorithm based on quantified measurements was ...

Optimizing predictive strategies for acute kidney injury after major vascular surgery.

Surgery
BACKGROUND: Postoperative acute kidney injury is common after major vascular surgery and is associated with increased morbidity, mortality, and cost. High-performance risk stratification using a machine learning model can inform strategies that mitig...