Neurology

Application of robot-assisted endoscopic technique in the treatment of patent ductus arteriosus in 106 children.

The objective is to evaluate and apply the robot-assisted endoscopic surgical technique for treatment of patent ductus arteriosus (PDA) in children. Clinical data of 106 children with PDA who underwent robot-assisted endoscopic operation were retrospectively analyzed from August, 2020 to March, 2022. Demographic and preoperative data were collected, including the patient's age, weight, diameter of...

Machine learning prediction of malignant middle cerebral artery infarction after mechanical thrombectomy for anterior circulation large vessel occlusion.

OBJECTIVE: Prediction of malignant middle cerebral artery infarction (MMI) could identify patients for early intervention. We trained and internally validated a ML model that predicts MMI following mechanical thrombectomy (MT) for ACLVO.

High-throughput 3DRA segmentation of brain vasculature and aneurysms using deep learning.

BACKGROUND AND OBJECTIVES: Automatic segmentation of the cerebral vasculature and aneurysms facilitates incidental detection of aneurysms. The assessm...

Geometric Deep Learning to Identify the Critical 3D Structural Features of the Optic Nerve Head for Glaucoma Diagnosis.

PURPOSE: To compare the performance of 2 relatively recent geometric deep learning techniques in diagnosing glaucoma from a single optical coherence t...

Review of Machine Learning and Artificial Intelligence (ML/AI) for the Pediatric Neurologist.

Artificial intelligence (AI) and a popular branch of AI known as machine learning (ML) are increasingly being utilized in medicine and to inform medic...

Cross-task cognitive workload recognition using a dynamic residual network with attention mechanism based on neurophysiological signals.

BACKGROUND AND OBJECTIVE: Evaluation of human cognitive workload (CW) helps improve the user experience of human-centered systems. To provide a contin...

A machine-learning algorithm for predicting brain age using Rey-Osterrieth complex figure tests of healthy participants.

OBJECTIVE: Neuropsychologists widely use the Rey-Osterrieth complex figure test (RCFT) as part of neuropsychological test batteries to evaluate cognit...

Deep learning for collateral evaluation in ischemic stroke with imbalanced data.

PURPOSE: Collateral evaluation is typically done using visual inspection of cerebral images and thus suffers from intra- and inter-rater variability. ...

Decoding of human identity by computer vision and neuronal vision.

Extracting meaning from a dynamic and variable flow of incoming information is a major goal of both natural and artificial intelligence. Computer visi...

Prediction of Tinnitus Treatment Outcomes Based on EEG Sensors and TFI Score Using Deep Learning.

Tinnitus is a hearing disorder that is characterized by the perception of sounds in the absence of an external source. Currently, there is no pharmace...

Robotic Instruments Inside the MRI Bore: Key Concepts and Evolving Paradigms in Imaging-enhanced Cranial Neurosurgery.

Intraoperative MRI has been increasingly used to robotically deliver electrodes and catheters into the human brain using a linear trajectory with grea...

Expectations and attitudes towards medical artificial intelligence: A qualitative study in the field of stroke.

INTRODUCTION: Artificial intelligence (AI) has the potential to transform clinical decision-making as we know it. Powered by sophisticated machine lea...

[Robotics in plastic surgery].

In recent years surgical robotic systems which were specifically developed for microsurgery have expanded the application of robotic-assisted surgery ...

Feasibility, Safety, and Functional Outcomes of Pelvic Hypothermia Induced Using a Rectal Cooling Device During Robot-Assisted Radical Prostatectomy: A Phase I/II Trial.

Radical prostatectomy (RP) is one of the standard treatments for localized prostate cancer. However, in terms of functional outcomes, there are aspec...

Efficacy of rehabilitation robot-assisted gait training on lower extremity dyskinesia in patients with Parkinson's disease: A systematic review and meta-analysis.

BACKGROUND: Robot-assisted training is used as a new rehabilitation training method for the treatment of motor dysfunction in neurological diseases. R...

Multi-speed transformer network for neurodegenerative disease assessment and activity recognition.

BACKGROUND AND OBJECTIVE: Neurodegenerative diseases are the most frequent age-related diseases. This type of disease, if not discovered in the initia...

Lesion-preserving unpaired image-to-image translation between MRI and CT from ischemic stroke patients.

PURPOSE: Multiple medical imaging modalities are used for clinical follow-up ischemic stroke analysis. Mixed-modality datasets are challenging, both f...

On lightmyography based muscle-machine interfaces for the efficient decoding of human gestures and forces.

Conventional muscle-machine interfaces like Electromyography (EMG), have significant drawbacks, such as crosstalk, a non-linear relationship between t...

Head CT deep learning model is highly accurate for early infarct estimation.

Non-contrast head CT (NCCT) is extremely insensitive for early (< 3-6 h) acute infarct identification. We developed a deep learning model that detects...

Dual-Modal Information Bottleneck Network for Seizure Detection.

In recent years, deep learning has shown very competitive performance in seizure detection. However, most of the currently used methods either convert...