Latest AI and machine learning research in surgery for healthcare professionals.
Liver disease is among the most common medical conditions in the world, leading to high rates of morbidity and death. Early identification of liver diseases enables prompt care, which may prevent many conditions from progressing to more serious stages, like cirrhosis or liver cancer. Traditionally, models often overlook the predictive importance of nutritional status and focus primarily on liver-s...
PURPOSE: Prehabilitation prior to colorectal cancer (CRC) surgery aims to improve functional capacity and postoperative outcomes, although results remain inconsistent due to variable programs. This study aimed to develop a predictive model for improvement in functional capacity during prehabilitation, using 6-min walk distance (6MWD) as the primary outcome. Identifying patients most likely to impr...
PURPOSE: Biochemical remission after transsphenoidal resection for acromegaly remains challenging, and early prognostication is limited. This study ap...
BACKGROUND: Traditional surgical skill assessment tools are inherently subjective, prone to interobserver variability, and place a substantial burden ...
To systematically characterize global publication trends, collaboration patterns, intellectual foundations, research hotspots, and emerging frontiers ...
Extended reality (XR) technologies have made remarkable progress and been widely applied in orthopedic surgical education, offering a valuable and inn...
To systematically characterize the global research landscape, collaboration patterns, and emerging trends in robotic-assisted dental, oral and maxillo...
Pre-deployment validation is commonly used to establish the safety and effectiveness of clinical artificial intelligence systems, but acceptable valid...
PURPOSE: This study compared traditional statistical models with machine learning algorithms for predicting surgically induced astigmatism after catar...
BACKGROUND AND AIMS: Acute Type A aortic dissection (ATAAD) is a surgical emergency in which delays in diagnosis, transfer, and operative activation i...
PURPOSE: This study aimed to develop a deep learning model based on magnetic resonance imaging (MRI) and clinical features for predicting PSM risk aft...
BACKGROUND: Robotic-assisted surgery is now an established part of contemporary orthopaedic practice, particularly in knee arthroplasty, where it has ...
OBJECTIVES: A bibliometric analysis of the evolution of robotic applications in oral, maxillofacial, and head and neck surgeries was conducted, and re...
Surgical resection for drug-resistant focal epilepsy relies on the precise presurgical localization of the epileptogenic zone (EZ). Although [1⁸F]FDG-...
Intraoperative video artificial intelligence (AI) has advanced rapidly in general surgery, however, its dependable clinical use remains uncommon. This...
BACKGROUND: Accurate prognostication after aneurysmal subarachnoid hemorrhage (aSAH) remains challenging. Conventional clinical and radiological gradi...
OBJECTIVE: The aim of this study was to develop and validate an anatomy-driven model that predicts gross-total resection (GTR) of skull base chondrosa...
BACKGROUND: Artificial intelligence (AI) is increasingly integrated into scientific publishing workflows, yet no study has formally evaluated the abil...
BACKGROUND: Randomized trials have shown equivocal outcomes between a direct aspiration as first-pass technique (ADAPT) and stent retriever (SR) strok...
BackgroundAccurate triage of trauma patients by Emergency Medical Services (EMS) is essential for optimal outcomes and resource allocation. The 2021 N...