Surgery

Comprehensive segmentation of focal cortical dysplasia by combining surface-based and whole-brain MRI deep learning algorithms: a proof-of-concept study.

Introduction.Focal cortical dysplasia type II (FCD II) is a significant cause of drug-resistant epilepsy, and the full surgical resection of the lesion is linked with excellent disease-free outcomes. Its imaging hallmark is the white matter hyperintense funnel-shaped transmantle sign on T2-FLAIR magnetic resonance imaging (MRI). Manual delineation of this abnormality is challenging and inconsisten...

Ultrasound-guided microwave ablation for breast tumors: current status and future perspectives.

Ultrasound (US)-guided microwave ablation (MWA) has emerged as a promising minimally invasive therapy for both benign and malignant breast tumors. This review comprehensively examines the current clinical status, technical principles, and therapeutic outcomes of US-guided MWA in breast tumor management. We discuss the biophysical mechanisms of MWA, its advantages over other ablation techniques-suc...

Creation of the Sonntag Virtual Reality Laboratory: A Framework for Innovation in Neurosurgical Training and Global Education.

BACKGROUND AND OBJECTIVES: Neurosurgical education requires innovative approaches to meet the demands of an evolving field and adequately train the ne...

[Innovative imaging techniques for urothelial carcinoma].

BACKGROUND: Imaging guides the staging of urothelial carcinoma and thus plays a central role in treatment decisions. Current guidelines reflect the in...

Artificial intelligence in estimating instantaneous wave-free ratio: a systematic literature review of techniques.

Fractional flow reserve (FFR) is an essential tool for evaluating coronary artery disease and directing percutaneous coronary intervention (PCI). The ...

Prognostic Significance of Lymph Node Ratio for Overall Survival in Patients with Lymph Node-Positive Bladder Cancer Post-Radical Cystectomy and Chemotherapy: A Multicenter Cohort Analysis.

BACKGROUND: The lymph node ratio (LNR) is gaining recognition as a prognostic biomarker for various malignant neoplasms. However, its prognostic role ...

Robust Distance Estimation with Out-of-distribution Detection in Ophthalmic Surgery.

OBJECTIVE: Micrometer-scale precision is vital for patient safety in ophthalmic surgery. Recent advancements in instrument-integrated optical sensors ...

Protocol for Personalised Prediction of Persistent Postsurgical Pain.

INTRODUCTION: Persistent postsurgical pain (PPSP) affects up to 15% of patients after major surgery, impairing physical function, quality of life and ...

RVO-ME: A Dual-Task OCT Dataset for Segmentation and Detection of Macular Lesions in Retinal Vein Occlusion.

Retinal vein occlusion (RVO) is one of the most common vision-threatening retinal diseases, with macular edema (ME) as its primary complication. Optic...

Evaluation of an artificial intelligence model for the identification of obstructive hydrocephalus on computed tomography of the head.

OBJECTIVE: Obstructive hydrocephalus is a critical radiographic finding requiring emergent treatment. Its identification on head CT by an AI model cou...

Single-cell Transcriptomic Profiling Reveals Diagnostic of T Cell-platelet Aggregates in Peripheral Blood for Coronary Vulnerable Plaques.

Acute coronary syndrome, driven by vulnerable plaque (VP) instability, is a major cause of cardiovascular mortality. Current diagnostic methods for VP...

Explainable machine learning model for predicting short-term outcomes in sepsis- induced coagulopathy.

BACKGROUND: Sepsis-Induced coagulopathy (SIC) is not only a common complication in the development process of sepsis but also related to poor prognosi...

Clinical Profile of Neurosurgical Consultations from the Emergency Department : A Retrospective Analysis.

OBJECTIVE: This study aimed to retrospectively analyze consultations requested from the emergency departments (EDs) to the neurosurgery (NS) departmen...

Development and validation of machine learning models for predicting operative duration in assisted reproductive technology procedures.

BACKGROUND: Accurate prediction of operative duration is essential for efficient scheduling and resource allocation in surgical settings. In assisted ...

Improving Diagnostic Precision in Thyroid Pathology by Synergistic Use of AI and Molecular Markers.

OBJECTIVES: For indeterminate thyroid nodules, molecular tests offer high negative predictive value (NPV), reducing missed malignancies, but have limi...

Slot-BERT: Self-supervised object discovery in surgical video.

Object-centric slot attention is a powerful framework for unsupervised learning of structured and explainable representations that can support reasoni...

Identification of cognitive phenotypes in temporal lobe epilepsy and genetic generalized epilepsy using robotic assessment.

BACKGROUND: Cognitive dysfunction is common in people with epilepsy (PWE). Although expectations exist for deficits based on diagnosis, phenotypic var...

Generative AI as Librarian: A New Model for Surgical Education.

Generative artificial intelligence (GAI) is anticipated to transform medical education, and many studies have already been published reporting its eff...

Development and Validation of a Machine Learning Tool for Plastic Surgery Residency Application Screening.

BACKGROUND: Applications to integrated plastic surgery residency programs have outpaced the growth of available positions. As a result, faculty must r...

Comparison of large language models and conventional machine learning in postoperative outcome prediction: a retrospective, multi-national development and validation study.

BACKGROUND: Conventional machine learning (ML) models for predicting surgical outcomes have limitations in generalizability We explored large language...