Surgery

End to End Proximal Anastomosis is the Sole Modifiable Variable in Risk Score for Loss of Patency of Aortobifemoral Artery Bypass After Index Operative Hospitalization.

OBJECTIVE: The purpose of this study was to create a risk score for loss of aorto-bifemoral artery bypass (ABF) patency utilizing preoperative, perioperative, and long term follow up variables in the Vascular Quality Initiative (VQI) database. METHODS: The VQI supra-inguinal arterial bypass module was queried from 2009-2025 and 4971 patients undergoing ABF had long term follow patency data and thu...

Cardiac magnetic resonance in patients with acute myocardial infarction: The added clinical value.

Cardiovascular magnetic resonance (CMR) has emerged as the reference noninvasive modality for a comprehensive assessment of myocardial injury following acute myocardial infarction (AMI). Beyond accurate quantification of ventricular volumes and ejection fraction, CMR uniquely enables in vivo characterization of the infarct size, the ischemic area at risk, microvascular obstruction, intramyocardial...

Chromovitrectomy: current evidence, emerging technologies, and practical applications in vitreoretinal surgery.

Chromovitrectomy has revolutionized vitreoretinal surgery by enabling the visualization of nearly transparent intraocular structures. This review eval...

Artificial Intelligence in Laparoscopic Skill Assessment: A Scoping Review.

OBJECTIVE: The purpose of this study was to describe and synthesize the existing literature regarding the application of artificial intelligence (AI) ...

Deep learning-automatic 3D analysis of regional condylar remodeling and skeletal relapse following bimaxillary surgery: a two-year follow-up study.

The aim of this study was to quantify postoperative regional condylar remodeling and its role in skeletal relapse after bimaxillary surgery using CBCT...

Hyperspectral Imaging for Breast-Conserving Surgery Margin Assessment: A Systematic Review.

CONTEXT.—: Breast-conserving surgery (BCS) offers comparable overall survival rates to mastectomy. However, 14% to 37% of cases require re-excision ow...

Deep learning for H&E-based meningioma molecular classification and outcome prediction: a retrospective cohort study.

BACKGROUND: The introduction of genomic profiling as a tool for molecular classification and clinical outcome prediction has revolutionised the care o...

Deep learning based on multiparametric MRI for differentiating benign from malignant PI-RADS 3 prostate lesions: a dual-center study.

To address the diagnostic challenge of indeterminate PI-RADS 3 prostate lesions, we developed a non-invasive deep learning radiomics model using multi...

Artificial intelligence system for anatomical landmark detection in rectovaginal fistula repair surgery: technical development and educational evaluation.

PURPOSE: Rectovaginal fistula from perineal body injury during delivery is rare, with limited case volumes preventing standardized protocols. We devel...

Enhanced vertebrae localization in CT volumes: a two-stage deep learning framework.

BACKGROUND: Vertebral landmark localization in computed tomography (CT) volumes is crucial for spinal pathological diagnosis, postoperative assessment...

Development, internal testing, and external validation of an interpretable machine-learning model for predicting imaging-confirmed in-hospital postoperative deep vein thrombosis in older patients with patellar fractures.

BACKGROUND: Older patients with patellar fractures may be at increased risk of postoperative deep vein thrombosis (DVT) because of trauma, perioperati...

A MOOC-based and high-fidelity surgical simulation-integrated clinical internship mode in optometry teaching for ophthalmology graduate students.

BACKGROUND: Clinical medicine postgraduates are expected to attain competencies equivalent to senior resident physicians. However, ophthalmology gradu...

Non-invasive periodontal screening using self-reported-oral-health (SROH) questionnaire and salivary biomarkers: development and validation of machine learning models.

BACKGROUND: Accurate and accessible screening tools for periodontitis are essential for early detection and disease prevention. This study evaluated a...

The application of large language models in bariatric surgery: A scoping review.

BACKGROUND: Exploratory applications of large language models within the specialized field of metabolic and bariatric surgery have begun to emerge. Ne...

TASC: a time-aware sequence clustering framework with uncertainty quantification for electronic health record trajectories.

Longitudinal electronic health record (EHR) trajectories are highly heterogeneous, sparse, and irregular, making unsupervised temporal pattern discove...

An interpretable machine learning model for preoperative risk stratification in paediatric congenital heart disease surgery: a retrospective cohort study.

BACKGROUND: Congenital heart disease (CHD), one of the most common birth defects, poses challenges to preoperative risk stratification due to its anat...

Understanding resistance in glioblastoma: insights into personalized and targeted therapeutic strategies.

Glioblastoma multiforme (GBM) is the most common and aggressive primary malignant brain tumor. Despite combined treatments, including surgical removal...

Results of a new model of videotraining for patients and caregivers for peritoneal dialysis: food for (AI) thought?

BACKGROUND: In an attempt to overcome the space-time limitations of traditional training we used a new telemedicine home-training model (Videotraining...

Machine learning versus clinical scoring systems for predicting poor wound healing after posterior surgery for thoracolumbar tuberculosis.

OBJECTIVE: Postoperative poor wound healing (PWH) is a significant complication following posterior surgery for thoracolumbar tuberculosis, leading to...

Machine Learning-Based Prediction of Independent Ambulation Following Intramedullary Spinal Cord Tumor Resection.

BACKGROUND AND OBJECTIVES: Intramedullary spinal cord tumor (IMSCT) resection carries a high risk of postoperative neurological deficit because of neu...