Neurosurgery

Semiautomated Approach for Muscle Weakness Detection in Clinical Texts.

The automated detection of adverse events in medical records might be a cost-effective solution for ...

Big Data, Big Impact: The Potential for Data Science in Neurosurgery.

[Artificial intelligence in neurosurgery].

BACKGROUND: Artificial intelligence (AI) in neurosurgery is becoming increasingly more important as ...

Letter to the Editor: "Bridging Machine Learning and Clinical Practice in Neurosurgery: Hurdles and Solutions".

Therapeutic approach comparison in bicuspid aortic valve aortopathy and clinical practice implications.

Bicuspid aortic valve (BAV) is the most common heart valve malformation, and it may be associated wi...

[Pulmonary nodule detection method based on convolutional neural network].

A method was proposed to detect pulmonary nodules in low-dose computed tomography (CT) images by two...

Convolutional Neural Networks for the Detection and Measurement of Cerebral Aneurysms on Magnetic Resonance Angiography.

Aneurysm size correlates with rupture risk and is important for treatment planning. User annotation ...

An Information Extraction Algorithm for Detecting Adverse Events in Neurosurgery Using Documents Written in a Natural Rich-in-Morphology Language.

Rich-in-morphology language, such as Russian, present a challenge for extraction of professional med...

Representation Learning of 3D Brain Angiograms, an Application for Cerebral Vasospasm Prediction.

Stroke is the fifth leading cause of death in the United States. Subarachnoid hemorrhage (SAH) is a ...

Prediction of Postoperative Hospital Stay with Deep Learning Based on 101 654 Operative Reports in Neurosurgery.

Electronic Health Records (EHRs) conceal a hidden knowledge that could be mined with data science to...

Outcome prediction of intracranial aneurysm treatment by flow diverters using machine learning.

OBJECTIVEFlow diverters (FDs) are designed to occlude intracranial aneurysms (IAs) while preserving ...

Natural and Artificial Intelligence in Neurosurgery: A Systematic Review.

BACKGROUND: Machine learning (ML) is a domain of artificial intelligence that allows computer algori...

Robotics in neurosurgery.

One of the first surgical specialties to adopt robotic procedures and one that continues to innovate

A Systematic Review on Machine Learning in Neurosurgery: The Future of Decision-Making in Patient Care.

Current practice of neurosurgery depends on clinical practice guidelines and evidence-based research...

[A Case of Infectious Pseudoaneurysm That Developed after Surgery for Local Recurrence of Rectal Cancer].

In February 2011, a male patient in his 60's underwent a low anterior resection and lateral lymph no...

The Changing Face of Technologically Integrated Neurosurgery: Today's High-Tech Operating Room.

Over the last decade, surgical technology in planning, mapping, optics, robotics, devices, and minim...

Artificial neural network for prediction of in-hospital mortality after open repair of ruptured abdominal aortic aneurysm.

Initial experience with a robotically operated video optical telescopic-microscope in cranial neurosurgery: feasibility, safety, and clinical applications.

OBJECTIVE The move toward better, more effective optical visualization in the field of neurosurgery ...

Robot-assisted procedures in pediatric neurosurgery.

OBJECTIVE During the last 3 decades, robotic technology has rapidly spread across several surgical f...

Endoscopic endonasal transsphenoidal surgery using the iArmS operation support robot: initial experience in 43 patients.

Objective The intelligent arm-support system, iArmS, which follows the surgeon's arm and automatical...

Augmented-reality integrated robotics in neurosurgery: are we there yet?

Surgical robots have captured the interest-if not the widespread acceptance-of spinal neurosurgeons....