BACKGROUND: Collateral circulation is associated with improved functional outcome in patients with large vessel occlusion acute ischemic stroke (AIS) who undergo reperfusion therapy. Assessment of collateral flow can be time consuming, subjective, an...
BACKGROUND: Given the significant cost and morbidity of patients undergoing lumbar fusion, accurate preoperative risk-stratification would be of great utility. We aim to develop a machine learning model for prediction of major complications and readm...
BACKGROUND: Magnified intraoperative visualization is of paramount importance during microsurgical procedures. Although the introduction of the operating microscope represented one of the most relevant innovations in modern neurosurgery, surgical vis...
OBJECTIVE: H3K27M mutation in gliomas has prognostic implications. Previous magnetic resonance imaging (MRI) studies have reported variable rates of tumoral enhancement, necrotic changes, and peritumoral edema in H3K27M-mutant gliomas, with no distin...
BACKGROUND: Readmission after spine surgery is costly and a relatively common occurrence. Previous research identified several risk factors for readmission; however, the conclusions remain equivocal. Machine learning algorithms offer a unique perspec...
OBJECTIVE: Computer vision (CV) is a subset of artificial intelligence that performs computations on image or video data, permitting the quantitative analysis of visual information. Common CV tasks that may be relevant to surgeons include image class...
BACKGROUND: Immediate and accurate detection of intracranial hemorrhages (ICHs) is essential to provide a good clinical outcome for patients with ICH. Artificial intelligence has the potential to provide this, but the assessment of these methods need...
BACKGROUND/OBJECTIVE: Technical skill acquisition is an essential component of neurosurgical training. Educational theory suggests that optimal learning and improvement in performance depends on the provision of objective feedback. Therefore, the aim...
OBJECTIVE: Ability to thrive after invasive and intensive treatment is an important parameter to assess in patients with glioblastoma multiforme (GBM). Karnofsky Performance Status (KPS) is used to identify those patients suitable for postoperative r...
OBJECTIVE: This study aims to evaluate the performance of convolutional neural networks (CNNs) trained with resting-state functional magnetic resonance imaging (rfMRI) latency data in the classification of patients with pediatric epilepsy from health...