Neurology

Memristive Neural Networks for Predicting Seizure Activity.

UNLABELLED: is to assess the possibilities of predicting epileptiform activity using the neuronal a...

Validation of deep learning techniques for quality augmentation in diffusion MRI for clinical studies.

The objective of this study is to evaluate the efficacy of deep learning (DL) techniques in improvin...

An extended clinical EEG dataset with 15,300 automatically labelled recordings for pathology decoding.

Automated clinical EEG analysis using machine learning (ML) methods is a growing EEG research area. ...

Effect of Lower Limb Exoskeleton on the Modulation of Neural Activity and Gait Classification.

Neurorehabilitation with robotic devices requires a paradigm shift to enhance human-robot interactio...

Technological Advances in Stroke Rehabilitation: Robotics and Virtual Reality.

Robotic technology and virtual reality (VR) have been widely studied technologies in stroke rehabili...

The use of deep learning models to predict progression-free survival in patients with neuroendocrine tumors.

The RAISE project assessed whether deep learning could improve early progression-free survival (PFS...

Early Detection of Optic Nerve Changes on Optical Coherence Tomography Using Deep Learning for Risk-Stratification of Papilledema and Glaucoma.

BACKGROUND: The use of artificial intelligence is becoming more prevalence in medicine with numerous...

Artificial intelligence for dementia-Applied models and digital health.

INTRODUCTION: The use of applied modeling in dementia risk prediction, diagnosis, and prognostics wi...

Rapid eye movement sleep loss associated cytomorphometric changes and neurodegeneration.

Rapid eye movement sleep (REMS) is essential for leading normal healthy living at least in higher-or...

Left recurrent nerve lymph node dissection in robotic esophagectomy for esophageal cancer without esophageal traction.

BACKGROUND: Because the robotic arm is located on the dorsal side of the patient, when the esophagus...

Transfer Learning on Electromyography (EMG) Tasks: Approaches and Beyond.

Machine learning on electromyography (EMG) has recently achieved remarkable success on various tasks...

CORR Insights®: Does the Presence of Missing Data Affect the Performance of the SORG Machine-learning Algorithm for Patients With Spinal Metastasis? Development of an Internet Application Algorithm.

A systematic review on intracranial aneurysm and hemorrhage detection using machine learning and deep learning techniques.

The risk of discovering an intracranial aneurysm during the initial screening and follow-up screenin...

ChatGPT vs Google for Queries Related to Dementia and Other Cognitive Decline: Comparison of Results.

BACKGROUND: People living with dementia or other cognitive decline and their caregivers (PLWD) incre...

Functional Outcome Prediction in Acute Ischemic Stroke Using a Fused Imaging and Clinical Deep Learning Model.

BACKGROUND: Predicting long-term clinical outcome based on the early acute ischemic stroke informati...

Accurate measurement of magnetic resonance parkinsonism index by a fully automatic and deep learning quantification pipeline.

OBJECTIVES: This study aims at a fully automatic pipeline for measuring the magnetic resonance parki...

Comparing the Lower-Limb Muscle Activation Patterns of Simulated Walking Using an End-Effector-Type Robot with Real Level and Stair Walking in Children with Spastic Bilateral Cerebral Palsy.

Cerebral palsy is a neurologic disorder caused by lesions on an immature brain, often resulting in s...

Novel use of robot-assisted gait rehabilitation in a patient with stroke and blindness.

Robot-assisted gait training (RAGT) is an effective adjunctive treatment for patients with stroke th...

Multimodal Deep Learning Classifier for Primary Open Angle Glaucoma Diagnosis Using Wide-Field Optic Nerve Head Cube Scans in Eyes With and Without High Myopia.

PRCIS: An optical coherence tomography (OCT)-based multimodal deep learning (DL) classification mode...

Reconfigurable neuromorphic computing block through integration of flash synapse arrays and super-steep neurons.

Neuromorphic computing (NC) architecture inspired by biological nervous systems has been actively st...

Differentiation between multiple sclerosis and neuromyelitis optica spectrum disorder using a deep learning model.

Multiple sclerosis (MS) and neuromyelitis optica spectrum disorder (NMOSD) are autoimmune inflammato...