Neurosurgery

Promises and Perils of Artificial Intelligence in Neurosurgery.

Artificial intelligence (AI)-facilitated clinical automation is expected to become increasingly prevalent in the near future. AI techniques may permit rapid and detailed analysis of the large quantities of clinical data generated in modern healthcare settings, at a level that is otherwise impossible by humans. Subsequently, AI may enhance clinical practice by pushing the limits of diagnostics, cli...

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 patient safety management or pharmacovigilance. Our group proposed an information extraction algorithm (IEA) for detecting adverse events in neurosurgery using documents written in a natural rich-in-morphology language. In this paper, we challenge to optimize and evaluate its performance for the det...

Classification of Intracranial Hemorrhage Subtypes Using Deep Learning on CT Scans.

Intracranial hemorrhage is a pathological condition that requires fast diagnosis and decision making. Recently, a neural network model for classificat...

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 the technology advances. This development can be m...

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 with the development of long-term complications, suc...

[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-dimensional convolutional neural network under th...

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 of aneurysm size is slow and tedious, particularly...

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 medical information. In this paper, we report on our ...

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 type of stroke often caused by the spontaneous rup...

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 tools. This is relevant for N.N. Burdenko Neurosurge...

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

OBJECTIVEFlow diverters (FDs) are designed to occlude intracranial aneurysms (IAs) while preserving flow to essential arteries. Incomplete occlusion e...

Natural and Artificial Intelligence in Neurosurgery: A Systematic Review.

BACKGROUND: Machine learning (ML) is a domain of artificial intelligence that allows computer algorithms to learn from experience without being explic...

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 publications that derive results using statistica...

[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 node dissection for lower rectal cancer. Due to larg...

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

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 minimally invasive techniques has changed the face of m...

Robotic paravertebral schwannoma resection at extreme locations of the thoracic cavity.

Solitary paravertebral schwannomas in the thoracic spine and lacking an intraspinal component are uncommon. These benign nerve sheath tumors are typic...