Japanese neurosurgery faces challenges such as a declining number of neurosurgeons and their concentration in urban areas. Particularly in rural areas, access to neurosurgical care for patients with conditions, such as stroke, is limited, raising con...
OBJECTIVE: To develop and evaluate machine learning (ML) approaches for muscle identification using intraoperative motor evoked potentials (MEPs), and to compare their performance to human experts.
BACKGROUND: Proper documentation is essential for patient care. The popularity of artificial intelligence (AI) offers the potential for improvements in neurosurgical note-writing. This study aimed to assess how AI can optimize documentation in neuros...
Cerebral aneurysm rupture, the predominant cause of non-traumatic subarachnoid hemorrhage, underscores the need for effective treatment and early detection methods. A study in Neurosurgical Review compared microsurgical clipping to endovascular thera...
BACKGROUND: Superior surgical skill improves surgical outcomes in endoscopic pituitary adenoma surgery. Video-based coaching programs, pioneered in professional sports, have shown promise in surgical training. In this study, we developed and assessed...
BMC medical informatics and decision making
Jul 31, 2024
BACKGROUND: Intraoperative neurophysiological monitoring (IOM) plays a pivotal role in enhancing patient safety during neurosurgical procedures. This vital technique involves the continuous measurement of evoked potentials to provide early warnings a...
With the current artificial intelligence (AI) boom, new innovative and accessible applications requiring minimal computer science expertise have been developed for discipline specific and mainstream purposes. Apple Intelligence, a new AI model develo...
PURPOSE: Artificial Intelligence (AI) has become increasingly integrated clinically within neurosurgical oncology. This report reviews the cutting-edge technologies impacting tumor treatment and outcomes.
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