AIMC Topic: Neurosurgical Procedures

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Development and multicenter validation of machine learning models for predicting postoperative pulmonary complications after neurosurgery.

Chinese medical journal
BACKGROUND: Postoperative pulmonary complications (PPCs) are major adverse events in neurosurgical patients. This study aimed to develop and validate machine learning models predicting PPCs after neurosurgery.

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...

Prediction of facial nerve outcomes after surgery for vestibular schwannoma using machine learning-based models: a systematic review and meta-analysis.

Neurosurgical review
Postoperative facial nerve (FN) dysfunction is associated with a significant impact on the quality of life of patients and can result in psychological stress and disorders such as depression and social isolation. Preoperative prediction of FN outcome...

Machine Learning Reveals Demographic Disparities in Palliative Care Timing Among Patients With Traumatic Brain Injury Receiving Neurosurgical Consultation.

Neurocritical care
BACKGROUND: Timely palliative care (PC) consultations offer demonstrable benefits for patients with traumatic brain injury (TBI), yet their implementation remains inconsistent. This study employs machine learning methods to identify distinct patient ...

Machine Learning Algorithms for Neurosurgical Preoperative Planning: A Scoping Review.

World neurosurgery
BACKGROUND AND OBJECTIVE: Preoperative neurosurgical planning is an important step in avoiding surgical complications, reducing morbidity, and improving patient safety. The incursion of machine learning (ML) in this domain has recently gained attenti...

Development and application of explainable artificial intelligence using machine learning classification for long-term facial nerve function after vestibular schwannoma surgery.

Journal of neuro-oncology
PURPOSE: Vestibular schwannomas (VSs) represent the most common cerebellopontine angle tumors, posing a challenge in preserving facial nerve (FN) function during surgery. We employed the Extreme Gradient Boosting machine learning classifier to predic...

Deep Learning Detection of Hand Motion During Microvascular Anastomosis Simulations Performed by Expert Cerebrovascular Neurosurgeons.

World neurosurgery
OBJECTIVE: Deep learning enables precise hand tracking without the need for physical sensors, allowing for unsupervised quantitative evaluation of surgical motion and tasks. We quantitatively assessed the hand motions of experienced cerebrovascular n...

Controversies in Artificial Intelligence in Neurosurgery.

Neurosurgery clinics of North America
Artificial intelligence (AI) has evolved from science fiction to a technology infiltrating everyday life. In neurosurgery, clinicians and researchers are exploring ways to implement this powerful tool to improve the safety and efficiency of the perio...

AI and neurosurgery: a new era of enhanced outcomes.

Neurosurgical review
Artificial Intelligence (AI) is revolutionizing neurosurgery by enhancing diagnostic accuracy, surgical planning, and personalized patient care. Despite challenges like data privacy and bias, AI's integration promises to transform surgical outcomes a...