Surgery

Development and Validation of an Interpretable Machine Learning Model for Predicting Distant Metastasis in Tongue Squamous Cell Carcinoma: A Multicentre Study.

INTRODUCTION AND AIMS: Distant metastasis (DM) in tongue squamous cell carcinoma is associated with poor prognosis. However, reliable tools for immediate postoperative risk prediction remain lacking. This study aimed to develop and validate an interpretable machine learning (ML) model for early risk stratification of DM. METHODS: This study included 752 patients from Sun Yat-sen Memorial Hospital ...

AI-driven navigated hematoma aspiration vs. conservative treatment for spontaneous intracerebral hemorrhage: study protocol for a randomized controlled trial.

BACKGROUND: Spontaneous intracerebral hemorrhage (ICH) remains one of the most devastating types of stroke, with high mortality and long-term disability. Minimally invasive hematoma evacuation techniques have been developed to improve outcomes by reducing hematoma volume while minimizing surgical trauma compared with conventional craniotomy or conservative treatment. Artificial intelligence (AI) a...

Artificial Intelligence in Patient Education: ChatGPT for Penile Prosthesis Surgery Counseling, a Likert Scale Analysis.

INTRODUCTION: Erectile dysfunction (ED) significantly impacts quality of life. For patients unresponsive to conservative treatments, penile prosthesis...

Development and External Validation of a Deep Learning Model to Predict Mortality in Aneurysmal Subarachnoid Hemorrhage Using Admission Computed Tomography.

BACKGROUND AND OBJECTIVES: Traditional prognostication after aneurysmal subarachnoid hemorrhage depends on subjective clinical grading and radiologica...

A robotic wound care patient for evidence-based surgical site infection research.

BACKGROUND: Surgical site infections (SSIs) are among the most common and preventable postoperative complications, yet existing preclinical models lac...

Current evidence and future directions for prophylactic anticoagulation therapy after severe spontaneous intracerebral hemorrhage: a narrative review.

Patients with spontaneous intracerebral hemorrhage (sICH) are at high risk for venous thromboembolism (VTE), a complication strongly associated with a...

Functional cortical network alterations in Parkinson's disease with wearing-off revealed by resting-state fNIRS and graph theory.

Wearing-off (WO) is a common motor complication in Parkinson's disease (PD), characterized by the re-emergence of symptoms before the next dose of dop...

A Datasheet for the INSIGHT Moorfields Cornea Anterior Segment Dataset (CADMUS).

PURPOSE: To describe Cornea Anterior Segment Dataset from Moorfields via INSIGHT (CADMUS), a large multimodal anterior segment imaging dataset develop...

Deep learning prediction of contrast extravasation versus intracranial hemorrhage after thrombectomy in patients with acute stroke.

From Bio-Interface Materials to Neural Integration: The Next-Generation Brain-Machine Interfaces Powered by Hydrogels.

Brain-machine interfaces (BMIs), which serve as revolutionary tools for neural recording, modulation, and rehabilitation, are highly dependent on the ...

Urinary extracellular vesicle miRNA signature reflects pancreatic islet stress in type 2 diabetes.

INTRODUCTION: Type 2 diabetes (T2D) is a progressive metabolic disorder characterized by insulin resistance and progressive β-cell dysfunction. Early ...

[Digital twins in uro-oncology].

BACKGROUND: Uro-oncology is moving toward precision medicine, driven by high-dimensional longitudinal data from imaging, pathology, molecular profilin...

Amyloidosis secondary to familial Mediterranean fever: machine learning-based prediction models.

OBJECTIVES: Familial Mediterranean Fever (FMF) is a monogenic autoinflammatory disease caused by MEFV mutations, with amyloidosis as its most severe c...

Enhancing CNN regressors with contour encoding and self-supervision for improved 3D/2D X-ray to CT registration in spinal surgery navigation.

With advances in deep learning, regression-based methods have shown promising results in 3D/2D medical image registration. However, strict intraoperat...

A Multicenter Prospective Study to Develop a Prediction Model for Postherpetic Neuralgia Using Clinical and Laboratory Indicators.

INTRODUCTION: Postherpetic neuralgia (PHN) is the most common and difficult-to-treat complication of herpes zoster (HZ). This complication not only ca...

Plaque-Level Machine Learning Prediction of Intraplaque Hemorrhage in Carotid Arteries Using Computed Tomography Angiography.

BACKGROUND: Carotid artery plaques, especially those with intraplaque hemorrhage (IPH), are significant contributors to ischemic stroke. Although high...

Few-shot learning for surgical phase recognition: Performance and generalization in cholecystectomy.

BACKGROUND AND OBJECTIVE: The automated recognition of surgical phases in intraoperative videos represents a critical milestone in the digital transfo...

The Effect of Age, Sex, and Body Mass Index on Spinopelvic Balance Throughout Childhood and Adolescence: An Automated 3D-Computed Tomography Study of 9,721 Pediatric Patients.

BACKGROUND: Spinopelvic assessment is critical for surgical planning. It is unknown if age, sex, and body mass index (BMI) influence pelvic orientatio...

Unlocking the mind: brain mapping for the exploratory quest of functional and cognitive networks in awake neurosurgery.

This retrospective study investigated the efficacy of intraoperative brain stimulation in 18 awake patients undergoing resection of intracranial lesio...

To include or not to include? A prescription from the pharmacy on how to use active learning-assisted screening in systematic reviews.

BACKGROUND: Systematic reviews are essential for evidence-based decision-making, but the screening stage is often labor-intensive and susceptible to h...