AI Medical Compendium Topic

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Neurosurgical Procedures

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The Co-Pilot Project in wartime: lessons from Lviv, Ukraine.

Neurosurgical focus
OBJECTIVE: The ongoing war in Ukraine has introduced many challenges to an already overburdened and resource-limited medical system. Longitudinal collaborations, material support, educational outreach, and surgical mentorship are essential for improv...

Accuracy and quality of ChatGPT-4o and Google Gemini performance on image-based neurosurgery board questions.

Neurosurgical review
Large-language models (LLMs) have shown the capability to effectively answer medical board examination questions. However, their ability to answer imagebased questions has not been examined. This study sought to evaluate the performance of two LLMs (...

Epilepsy surgery candidate identification with artificial intelligence: An implementation study.

Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia
BACKGROUND: To (a) evaluate the effect of a machine learning algorithm in the identification of patients suitable for epilepsy surgery evaluation, and (b) examine the performance of a large language model (LLM) in the collation of key pieces of infor...

Comparison of surgical approaches to the hippocampal formation with artificial intelligence.

Neurosurgical review
The relatively complex functional anatomy of the mediobasal temporal region makes surgical approaches to this area challenging. Several studies describe various surgical approaches, along with their combinations and modifications, to reach lesions of...

Performance evaluation of ChatGPT-4.0 and Gemini on image-based neurosurgery board practice questions: A comparative analysis.

Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia
INTRODUCTION: Artificial intelligence (AI) has gained significant attention in medicine, particularly in neurosurgery, where its potential is often discussed and occasionally feared. Large language models (LLMs), such as ChatGPT-4.0 (OpenAI) and Gemi...

Ethical Concerns of AI in Neurosurgery: A Systematic Review.

Brain and behavior
BACKGROUND: The relentless integration of Artificial Intelligence (AI) into neurosurgery necessitates a meticulous exploration of the associated ethical concerns. This systematic review focuses on synthesizing empirical studies, reviews, and opinion ...

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

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: Neurosurgery demands high precision, and robotic-assisted systems are increasingly employed to enhance surgical outcomes. This study focuses on a hybrid robotic-assisted system for neurosurgery, addressing forward and inverse kinematics, ...

[Real-Time Artificial Intelligence Assistance in Neuroendovascular Surgery].

No shinkei geka. Neurological surgery
In neuroendovascular surgery, operators must manipulate devices, such as microcatheters and guidewires, with millimeter precision while simultaneously monitoring multiple areas across up to four radiography monitors. Although both operators and assis...

The role of artificial intelligence in diagnostic neurosurgery: a systematic review.

Neurosurgical review
BACKGROUND: Artificial intelligence (AI) is increasingly applied in diagnostic neurosurgery, enhancing precision and decision-making in neuro-oncology, vascular, functional, and spinal subspecialties. Despite its potential, variability in outcomes ne...

Development and validation of a predictive machine learning model for postoperative long-term diabetes insipidus following transsphenoidal surgery for sellar lesions.

Clinical neurology and neurosurgery
OBJECTIVE: Diabetes Insipidus (DI) is a common complication that occurs following transsphenoidal surgery for sellar lesions. DI is usually transient but can be permanent in select patients. Prior studies have described preoperative risk factors for ...