Surgery

Personalised thrombo-embolic risk prediction after endometrial cancer surgery: an explainable AI approach using SHAP.

To address the clinical challenge of postoperative lower extremity deep vein thrombosis (LEDVT) in endometrial cancer care, this study establishes an explainable machine learning framework for personalized risk prediction. Utilizing perioperative data from 841 patients across multiple centers, we evaluated 26 machine learning algorithms combined with diverse data augmentation techniques. The Suppo...

Perception in action: a robotic system that can teach itself to melodiously play music by ear.

Learning to imitate nuanced motor behaviour by perceiving someone's actions is a human ability central to non-verbal communication, interaction and collaboration. Despite extensive psychophysics research, robotic systems do not yet seamlessly bridge the gap between perception and action. We demonstrate a perceptual learning algorithm that can replicate a melody after hearing it once by using a phy...

PIVOTS: Aligning unseen structures using preoperative to intraoperative volume-to-surface registration for liver navigation.

Non-rigid registration is essential for augmented reality-guided laparoscopic liver surgery, as it enables the fusion of preoperative information such...

Non-invasive somatotopic proprioceptive feedback for closed-loop robotic hand aperture control.

Objective.Current robotic prostheses developed for individuals with transradial amputation often lack physiological feedback, particularly propriocept...

EasyVis2: a real-time multi-view 3D visualization system for laparoscopic surgery training enhanced by a deep neural network YOLOv8-pose.

Minimally invasive laparoscopic surgery often suffers from limited depth perception and constrained visual fields. To address these limitations, we in...

Addendum to "Predicting treatment pathways in Class II malocclusion patients using machine learning: A comparative study of four algorithms for classifying camouflage, growth modulation, and surgical decisions" [Int Orthod. 24 (2026) 101070].

OBJECTIVES: The aim of this study was to develop a machine learning model to assist in treatment decision-making for surgery, camouflage, and growth m...

Artificial Intelligence in Neuroradiology: A Review of FDA-regulated Algorithms.

Artificial intelligence (AI) is increasingly integrated into neuroradiology practice, with a growing number of FDA-cleared algorithms now supporting t...

Prediction of Neurological Outcome and Mortality in Cardiac Arrest Patients: An Explainable Machine Learning Study Integrating HRV, EEG, and Clinical Features.

OBJECTIVE: Early and accurate prediction of neurological outcomes and mortality in comatose patients after cardiac arrest remains challenging. Multimo...

Global evolution of robot-assisted cholecystectomy research in the era of artificial intelligence: a bibliometric and knowledge-mapping study.

OBJECTIVE: To systematically map the global evolution, collaborative networks, knowledge structure, and emerging research hotspots in robot-assisted c...

Development and validation of an early prediction model for bee-sting-induced acute kidney injury using machine learning.

Acute kidney injury (AKI) is a severe and frequent complication following bee stings, with a reported incidence of 30-50%. Early identification is cli...

The eye sees what the mind knows: Eye tracking and artificial intelligence to assess surgical resident level of expertise.

BACKGROUND: Surgical education continues to strive to move beyond traditional time-based competency metrics. As gaze behaviors can reflect underlying ...

Tibial diaphyseal malunion: A problem-oriented approach to assessment and correction.

Tibial shaft fractures are the most common long bone injuries, and malunion remains a significant complication despite advances in fixation. Tibial di...

Interpretable and non-linear machine learning models for quantitative ICG perfusion assessment in colorectal cancer anastomosis: A feasibility study.

BACKGROUND: Anastomotic leakage (AL) remains a major complication after colorectal cancer surgery (CCS). Intraoperative indocyanine green (ICG) fluore...

3D craniofacial generative model for surgical planning in mandibular reconstruction.

Mandibular reconstruction following segmental resection for oral tumors is a complex procedure necessitating precise restoration of both masticatory f...

Evaluating Injection Laryngoplasty Skills Using a Foundation Model: A Feasibility Study.

OBJECTIVES: To evaluate the construct validity of a commercially available multimodal foundation model (Google Gemini 2.5 Pro) in assessing simulated ...

Emerging applications of traditional and generative artificial intelligence in Liver Transplantation.

Artificial intelligence (AI) has emerged as a transformative force in liver transplantation (LT), spanning patient selection, donor-recipient matching...

[Clinical practice guidelines for the application of intelligent technology in spinal surgery (2026 edition)].

In response to the challenges of insufficient precision and limited safety associated with traditional techniques in the diagnosis and treatment of co...

Digital Pathology in Head and Neck Squamous Cell Carcinoma: Translational Advances and Clinical Integration for Pathologists, Oncologists, and Surgeons.

PURPOSE: Artificial intelligence (AI)-enabled digital pathology has advanced rapidly in head and neck squamous cell carcinoma (HNSCC), but its readine...

DSA-NRP: No-Reflow Prediction from Angiographic Perfusion Dynamics in Stroke EVT.

Following successful large-vessel recanalization via endovascular thrombectomy (EVT) for acute ischemic stroke (AIS), some patients experience a compl...

AI-Supported, Integrative Prediction of Postoperative Delirium: Protocol for the CONFUSED Study.

BACKGROUND: Postoperative delirium (POD) is a frequent and serious complication in older surgical patients, characterized by acute cognitive dysfuncti...