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Neurosurgery

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

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Apple Intelligence in neurosurgery.

With the current artificial intelligence (AI) boom, new innovative and accessible applications requi...

Automated Method for Intracranial Aneurysm Classification Using Deep Learning.

Intracranial aneurysm (IA) is now a common term closely associated with subarachnoid hemorrhage. IA ...

Assessing accuracy and consistency in intracranial aneurysm sizing: human expertise vs. artificial intelligence.

Intracranial aneurysms (IAs) are a common vascular pathology and are associated with a risk of ruptu...

A comprehensive investigation of morphological features responsible for cerebral aneurysm rupture using machine learning.

Cerebral aneurysms are a silent yet prevalent condition that affects a significant global population...

Machine Learning Based Prediction of Post-operative Infrarenal Endograft Apposition for Abdominal Aortic Aneurysms.

OBJECTIVE: Challenging infrarenal aortic neck characteristics have been associated with an increased...

Classification, detection, and segmentation performance of image-based AI in intracranial aneurysm: a systematic review.

BACKGROUND: The detection and management of intracranial aneurysms (IAs) are vital to prevent life-t...

7 T and beyond: toward a synergy between fMRI-based presurgical mapping at ultrahigh magnetic fields, AI, and robotic neurosurgery.

Presurgical evaluation with functional magnetic resonance imaging (fMRI) can reduce postsurgical mor...

Text-to-video generative artificial intelligence: sora in neurosurgery.

Artificial intelligence (AI) has increased in popularity in neurosurgery, with recent interest in ge...

URCA: Uncertainty-based region clipping algorithm for semi-supervised medical image segmentation.

BACKGROUND AND OBJECTIVE: Training convolutional neural networks based on large amount of labeled da...

Improving intracranial aneurysms image quality and diagnostic confidence with deep learning reconstruction in craniocervical CT angiography.

BACKGROUND: The diagnostic impact of deep learning computed tomography (CT) reconstruction on intrac...

Dissatisfaction-considered waiting time prediction for outpatients with interpretable machine learning.

Long waiting time in outpatient departments is a crucial factor in patient dissatisfaction. We aim t...

Machine learning models on a web application to predict short-term postoperative outcomes following anterior cervical discectomy and fusion.

BACKGROUND: The frequency of anterior cervical discectomy and fusion (ACDF) has increased up to 400%...

Can Artificial Intelligence Mitigate Missed Diagnoses by Generating Differential Diagnoses for Neurosurgeons?

BACKGROUND/OBJECTIVE: Neurosurgery emphasizes the criticality of accurate differential diagnoses, wi...

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

OBJECTIVE: To evaluate variability in aneurysm detection and the potential of artificial intelligenc...

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