Latest AI and machine learning research in neurosurgery for healthcare professionals.
The field of robotic microsurgery and micro-manipulation has undergone a profound evolution in recent years, particularly with regard to the accuracy, precision, versatility, and dexterity. These advancements have the potential to revolutionize high-precision biomedical procedures, such as neurosurgery, vitreoretinal surgery, and cell micro-manipulation. However, a critical challenge in developing...
OBJECTIVE: Computed tomography angiography (CTA) is the most widely used imaging modality for intracranial aneurysm (IA) management, yet it remains inferior to digital subtraction angiography (DSA) for IA detection, particularly of small IAs in the cavernous carotid region. The authors evaluated a deep learning pipeline for segmentation of vessels and IAs from CTA using coregistered, segmented DSA...
Robotic liver resection is a new platform for minimally invasive liver resection, and its functional advantages are expected to reduce or overcome the...
Due to the need to achieve precise operations during surgery, in order to prevent hand tremors and poor surgical field of view, more and more surgical...
To examine the application value of 3D Slicer software assisted domestic frameless stereotactic robot in biopsy of intracranial lesions. A retrospec...
Significant progress has been made in the use of artificial intelligence (AI) in clinical medicine over the past decade, but the clinical development ...
The application of surgical robots in neurosurgery has formed a rapidly developing and fascinating new field that is revolutionizing the way neurosurg...
Traditional methods to access subcortical structures involve the use of anatomical atlases and high precision stereotaxic frames but suffer from signi...
In this study, we update the evaluation of the Russian GPT3 model presented in our previous paper in predicting the length of stay (LOS) in neurosurge...
Gliomas are the most common neuroepithelial brain tumors, different by various biological tissue types and prognosis. They could be graded with four l...
Patients, relatives, doctors, and healthcare providers anticipate the evidence-based length of stay (LOS) prediction in neurosurgery. This study aimed...
For almost a century, classical statistical methods including exponential smoothing and autoregression integrated moving averages (ARIMA) have been pr...
OBJECTIVE: The application of robots in the field of pedicle screw placement has achieved great success. However, decompressive laminectomy, a step th...
OBJECTIVE: The utility of robotic instrumentation is expanding in neurosurgery. Despite this, successful examples of robotic implementation for endosc...
Deep learning (DL) is a powerful machine learning technique that has increasingly been used to predict surgical outcomes. However, the large quantity ...
The umbilical cord is an organ that circulates oxygen and nutrition from mother to fetus during pregnancy. This study aims to classify the umbilical c...
Objectives : To evaluate whether virtual partial nephrectomy images could help surgeons identify vascular and collecting system around tumors during a...