BACKGROUND: Artificial Intelligence (AI) has emerged as a transformative tool in medicine, particularly addressing neurosurgical challenges such as complex anatomical delineation and intraoperative decision-making. Despite advancements in diagnostic ...
Wearable technology, combined with artificial intelligence (AI) and machine learning (ML) algorithms, opens up new frontiers for continuously monitoring physiological or behavioural data, allowing the identification of stroke risk factors at an earli...
Gliomas are the most common primary tumors of the central nervous system, and advances in genetics and molecular medicine have significantly transformed their classification and treatment. This study aims to predict the IDH1 genotype in gliomas using...
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...
Traumatic brain injury (TBI) is a significant global health issue with high morbidity and mortality rates. Recent studies have shown that machine learning algorithms outperform traditional logistic regression models in predicting functional outcomes ...
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 (...
Malignant cerebral edema (MCE) is a severe complication of acute ischemic stroke, with high mortality rates. Early and accurate prediction of MCE is critical for initiating timely interventions such as decompressive hemicraniectomy. Artificial intell...
The objective of this study was to develop and evaluate automated machine learning (aML) models for predicting short-term (1-month) and medium-term (3-month) functional outcomes [Modified Rankin Scale (mRS)] in patients suffering from poor-grade aneu...
Parkinson's Disease (PD) is a growing burden with varied clinical manifestations and responses to Subthalamic Nucleus Deep Brain Stimulation (STN-DBS). At present, there is no effective and simple machine learning model based on comprehensive clinica...
In the multidisciplinary treatment of cerebrovascular diseases, specialists from different disciplines strive to develop patient-specific treatment recommendations. ChatGPT is a natural language processing chatbot with increasing applicability in med...