Surgery

Improving Wheelchair Transfers: Usability Study of a Robotic Transfer System.

OBJECTIVES: Transfers between wheelchairs and beds pose injury risks to users and caregivers, with conventional devices often inefficient and unsafe. The Powered Personal Transfer System-a no-lift solution integrating an electric powered wheelchair and hospital bed-aims to improve safety and efficiency. This study evaluated (1) the usability of the powered personal transfer system compared with cu...

Efficacy and comparative performance of machine learning models for stroke risk prediction in hypertensive patients: A systematic review and meta-analysis.

BACKGROUND: Stroke poses a significant health burden among hypertensive patients, where traditional risk models often lack precision. Machine learning (ML) has shown promise in enhancing prediction accuracy by integrating diverse data sources. METHODS: Following PRISMA guidelines, we searched 5 databases from inception to September 2025. Eligible studies reported the performance of ML models in hy...

Artificial Intelligence for Suturing and Knot-tying Skills Assessment: A Systematic Review.

BACKGROUND: Artificial intelligence (AI) has great potential for surgical skill training and assessment. However, the heterogeneity of AI models for s...

Interpretable fusion deep learning on super-resolution MRI for perineural invasion prediction in pancreatic ductal adenocarcinoma: a multicenter study.

PURPOSE: To develop an interpretable fusion deep learning model based on super-resolution (SR) MRI for predicting preoperative perineural invasion (PN...

Diagnostic Performance of AI-Assisted Coronary CT Angiography: A Systematic Review and Meta-Analysis.

BACKGROUND: Coronary computed tomography angiography (CCTA) is vital for diagnosing ischemic heart disease, yet its accuracy is unreliable due to vary...

Brain connectivity predict surgical outcomes of low-grade epilepsy-associated neuroepithelial tumors.

OBJECTIVE: Low-grade epilepsy-associated neuroepithelial tumors (LEATs) often cause drug-resistant epilepsy. Despite complete resection of these lesio...

[Expert consensus on neurosurgical robot-assisted deep brain stimulation surgery (2026 edition)].

Robot-assisted deep brain stimulation (DBS) surgical systems in neurosurgery have demonstrated significant advantages in enhancing operative precision...

Artificial intelligence and machine learning applications in ambulatory surgery - A systematic review.

BACKGROUND: We aimed to systematically review applications of artificial intelligence (AI) technologies for ambulatory surgical patients. METHODS: We ...

Preoperative Identification of Lymph Node Metastasis in Colorectal Cancer Using Noninvasive Circulating Tumor DNA Methylation Signatures: Results From a Prospective Study.

BACKGROUND: Lymph node metastasis is important for the management and surgical procedures of patients with colorectal cancer. Preoperative identificat...

Development and Validation of an Interpretable Machine Learning Model for Predicting Early Fusion After Anterior Cervical Discectomy and Fusion.

STUDY DESIGN: Retrospective case-control study. OBJECTIVES: This study aimed to develop and preliminarily validate a machine learning (ML) model for p...

Industry 6.0 capabilities in orthopaedics: Towards hyper-personalized and autonomous surgical care.

BACKGROUND: Industry 6.0 represents the next frontier in technological evolution, integrating artificial intelligence (AI), autonomous robotics, digit...

Leveraging artificial intelligence for surgical site infection surveillance: A comparison of 5 large language models.

We conducted a retrospective study to evaluate the performance of 5 large language models in detecting surgical site infections (SSIs), compared with ...

Machine Learning-Based Prediction for Axial Pain Following Expansive Unilateral Open-Door Laminoplasty: A Retrospective Cohort Study.

INTRODUCTION: Axial pain is a common complication following expansive unilateral open-door laminoplasty (ELAP); however, traditional statistical metho...

Biometric facial recognition after bimaxillary orthognathic surgery.

Orthognathic surgery is performed to correct dentoskeletal deformities and restore maxillomandibular symmetry. These changes may affect biometric iden...

Predicting and Early Detection of Delirium through Motion Patterns: A Narrative Review.

Delirium is a common acute neuropsychiatric syndrome, and its early detection may improve clinical outcomes. This narrative review synthesized finding...

AI-Driven CT-MRI Image Fusion and Segmentation for Automatic Preoperative Planning of ACL Reconstruction: Development and Application.

BACKGROUND: The goals of this study were to develop an artificial intelligence (AI)-driven automated preoperative planning system for anterior cruciat...

Prediction model for the risk of vitreous haemorrhage after vitrectomy combined with intraocular injection for the treatment of proliferative diabetic retinopathy.

OBJECTIVE: The purpose of this study was to develop a lightweight multimodal deep learning model for accurately predicting the risk of postoperative v...

Development and multicenter validation of a machine learning model for postoperative sepsis risk in critically Ill traumatic spinal injury patients.

OBJECTIVE: To develop and validate a machine learning model for postoperative sepsis in critically ill traumatic spinal injury (TSI) patients, a frequ...

Evaluating the Performance and Fragility of Large Language Models on the Self-Assessment for Neurological Surgeons.

BACKGROUND AND OBJECTIVES: The Congress of Neurological Surgeons Self-Assessment for Neurological Surgeons questions are widely used by neurosurgical ...

Artificial intelligence-driven 3-dimensional simulation system for enhanced preoperative planning in gastric cancer surgery: a retrospective validation study.

BACKGROUND: Few studies have developed artificial intelligence (AI) systems for the automatic recognition of the anatomy of the stomach, a dynamic org...