Neurosurgery

MACHINE LEARNING VERSUS PENALISED LOGISTIC REGRESSION FOR PREDICTING IN-HOSPITAL MORTALITY IN RUPTURED ABDOMINAL AORTIC ANEURYSM: A COMPARISON USING A UNIFORM VALIDATION FRAMEWORK.

BACKGROUND: Ruptured abdominal aortic aneurysm (rAAA) remains associated with substantial in-hospita...

A Combined Clinical/MRI Deep Learning Model for Estimating Outcomes After Percutaneous Transforaminal Endoscopic Discectomy.

BACKGROUND: Percutaneous transforaminal endoscopic discectomy (PTED) is a common treatment for lumba...

Deep Learning-based Automated Vessel Extraction for VR Image Creation From Cerebral TOF-MRA.

RATIONALE AND OBJECTIVES: Accurate and efficient three-dimensional visualization of cerebral vascula...

Predictive simulation of coil mechanics uncovers shape-driven determinants of endovascular coiling efficacy in intracranial aneurysms.

Endovascular coiling is a minimally invasive therapeutic option for intracranial aneurysm (IA). This...

The Influence of Patient Persona and Affective Framing on Management Recommendations of ChatGPT, Gemini and Claude for Unruptured Intracranial Aneurysms: A Comparative Benchmarking Study.

Patients increasingly consult large language models (LLMs) before specialist review and may do so in...

Accuracy and Readability of Generative Artificial Intelligence for Vascular Surgery Patients: A Specialist Based Evaluation Highlighting the Current Landscape of Safety Risks and Accessibility Gaps.

OBJECTIVE: Patients frequently seek health information and medical advice from chatbots instead of c...

Machine Learning Based on Multiparametric Features from Dual-Layer Detector Spectral CT for Identifying Ulcer-Like Projection in Aortic Intramural Hematoma.

Aortic intramural hematoma (IMH) is a high-risk subtype of acute aortic syndrome (AAS). The presence...

An interpretable machine learning approach to predict left ventricular aneurysm formation following primary PCI in STEMI: A retrospective study with independent external validation.

BACKGROUND: Left ventricular aneurysm (LVA) remains a clinically important structural complication a...

Automated Generation and Human Evaluation of Neurosurgical Board Examination Self-Assessment Questions.

BACKGROUND AND OBJECTIVES: Multiple-choice questions are the primary assessment format for neurosurg...

Artificial Intelligence in Neurosurgery: From Technical Metrics to Deployable Clinical Evidence.

Letter: Artificial Intelligence and the Jagged Frontier of Clinical Reasoning: Lessons from Neurosurgery.

[Overview and conclusions of the STROKE data platform of the National Laboratory for Translational Neuroscience and the associated clinical studies].

Acute ischemic and hemorrhagic stroke are among the leading causes of mortality and long-term disabi...

Data-centric physics-inspired deep learning framework for saturation artifact removal in optical coherence tomography.

In Fourier-domain optical coherence tomography (FD-OCT) imaging, saturation of the data acquisition ...

Patient and physician perspectives on large language model generated responses about brain aneurysm.

PURPOSE: Large language models (LLMs) are becoming increasingly popular in medicine and neurosurgery...

Optimizing the mathematical model and technical standards for unilateral biportal endoscopic spinal surgery through machine learning-based video analysis.

OBJECTIVE: To enhance the efficacy of the unilateral biportal endoscopic spinal procedure, the spina...

Intraoperative technological advances and new frontiers in precision glioma surgery.

BACKGROUND: Diffuse gliomas remain among the most surgically challenging tumors, characterized by th...

Enhancing decision-making in surgery for a large temporocorneal meningioma through an explainable human-AI collaboration: a case report.

BACKGROUND: Meningiomas, particularly large temporocorneal meningiomas, pose significant surgical ch...

Vibe Coding in Neurosurgery: Bridging the Gap Between Clinical Needs and Digital Innovation-A Narrative Review and Practical Perspective.

BackgroundArtificial intelligence (AI) and machine learning are transforming neurosurgical research ...

Adaptive learning rate methodologies and clipping mechanisms based upon gradient entropy.

Serving as a pivotal parameter during deep learning training processes, learning rate plays a crucia...

End-to-End Autonomous Quantification of Brain Aneurysm and Parent Artery Morphology at CT Angiography.

Purpose To develop and validate an end-to-end autonomous platform for the quantification and visuali...

A single-source preoperative prediction model for recurrent lumbar disc herniation after primary discectomy: Development and internal validation in the SPORT registry.

BACKGROUND: Recurrent lumbar disc herniation (rLDH) follows primary discectomy in 5% to 25% of patie...