Surgery

Neurosurgery

Latest AI and machine learning research in neurosurgery for healthcare professionals.

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Artificial intelligence in neurosurgery: a systematic review of applications, model comparisons, and ethical implications.

BACKGROUND: Artificial Intelligence (AI) has emerged as a transformative tool in medicine, particula...

Machine learning decision support model construction for craniotomy approach of pineal region tumors based on MRI images.

BACKGROUND: Pineal region tumors (PRTs) are rare but deep-seated brain tumors, and complete surgical...

Machine learning for clinical outcome prediction in cerebrovascular and endovascular neurosurgery: systematic review and meta-analysis.

BACKGROUND: Machine learning (ML) may be superior to traditional methods for clinical outcome predic...

A fully automatic radiomics pipeline for postoperative facial nerve function prediction of vestibular schwannoma.

Vestibular schwannoma (VS) is the most prevalent intracranial schwannoma. Surgery is one of the opti...

Current Trends and Future Directions in Lumbar Spine Surgery: A Review of Emerging Techniques and Evolving Management Paradigms.

: Lumbar spine surgery has undergone significant technological transformation in recent years, drive...

Automatic CTA analysis for blood vessels and aneurysm features extraction in EVAR planning.

Endovascular Aneurysm Repair (EVAR) is a minimally invasive procedure crucial for treating abdominal...

Promptable segmentation of CT lung lesions based on improved U-Net and Segment Anything model (SAM).

BackgroundComputed tomography (CT) is widely used in clinical diagnosis of lung diseases. The automa...

AI-Driven Advances in Parkinson's Disease Neurosurgery: Enhancing Patient Selection, Trial Efficiency, and Therapeutic Outcomes.

Parkinson's disease (PD) is a progressive neurodegenerative disorder marked by motor and non-motor d...

Development and Validation of a Sham-AI Model for Intracranial Aneurysm Detection at CT Angiography.

Purpose To evaluate a sham-artificial intelligence (AI) model acting as a placebo control for a stan...

Battle of the authors: Comparing neurosurgery articles written by humans and AI.

BACKGROUND: The advancement of artificial intelligence (AI) has led to its application in various fi...

Ethical Concerns of AI in Neurosurgery: A Systematic Review.

BACKGROUND: The relentless integration of Artificial Intelligence (AI) into neurosurgery necessitate...

Full Study, Model Verification, and Control of a Five Degrees of Freedom Hybrid Robotic-Assisted System for Neurosurgery.

BACKGROUND: Neurosurgery demands high precision, and robotic-assisted systems are increasingly emplo...

Effect of Laminectomy Methods on the Surgical Safety of Automatic Laminectomy Robot.

BACKGROUND: The efficacy of laminectomy procedures is contingent on the method of resection. The obj...

Deep learning-based fine-grained assessment of aneurysm wall characteristics using 4D-CT angiography.

PURPOSE: This study proposes a novel deep learning-based approach for aneurysm wall characteristics,...

Systematic Review of Radiomics and Artificial Intelligence in Intracranial Aneurysm Management.

Intracranial aneurysms, with an annual incidence of 2%-3%, reflect a rare disease associated with si...

Intelligent Control to Suppress Epileptic Seizures in the Amygdala: In Silico Investigation Using a Network of Izhikevich Neurons.

Closed-loop electricalstimulation of brain structures is one of the most promising techniques to sup...

Letter to Editor Regarding "Use of Artificial Intelligence Software to Detect Intracranial Aneurysms: A Comprehensive Stroke Center Experience".

Artificial intelligence (AI) is increasingly significant in neurosurgery, enhancing differential dia...

Development of machine learning prediction model for AKI after craniotomy and evacuation of hematoma in craniocerebral trauma.

The aim of this study was to develop a machine-learning prediction model for AKI after craniotomy an...

Unsupervised Denoising and Super-Resolution of Vascular Flow Data by Physics-Informed Machine Learning.

We present an unsupervised deep learning method to perform flow denoising and super-resolution witho...

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