Neurology

Mechanical Neural Networks with Explicit and Robust Neurons.

Mechanical computing provides an information processing method to realize sensing-analyzing-actuatio...

Validation of artificial intelligence for epileptic seizure detection: Moving from research into the clinic.

Machine learning predicts cerebral vasospasm in patients with subarachnoid haemorrhage.

BACKGROUND: Cerebral vasospasm (CV) is a feared complication which occurs after 20-40% of subarachno...

Multiclass Classification of Visual Electroencephalogram Based on Channel Selection, Minimum Norm Estimation Algorithm, and Deep Network Architectures.

This work addresses the challenge of classifying multiclass visual EEG signals into 40 classes for b...

Machine learning of dissection photographs and surface scanning for quantitative 3D neuropathology.

We present open-source tools for three-dimensional (3D) analysis of photographs of dissected slices ...

A Neurosurgical Readmissions Reduction Program in an Academic Hospital Leveraging Machine Learning, Workflow Analysis, and Simulation.

BACKGROUND:  Predicting 30-day hospital readmissions is crucial for improving patient outcomes, opti...

SleepFC: Feature Pyramid and Cross-Scale Context Learning for Sleep Staging.

Automated sleep staging is essential to assess sleep quality and treat sleep disorders, so the issue...

Super-resolution Deep Learning Reconstruction for 3D Brain MR Imaging: Improvement of Cranial Nerve Depiction and Interobserver Agreement in Evaluations of Neurovascular Conflict.

RATIONALE AND OBJECTIVES: To determine if super-resolution deep learning reconstruction (SR-DLR) imp...

Rapid Electroencephalography and Artificial Intelligence in the Detection and Management of Nonconvulsive Seizures.

STUDY OBJECTIVE: Nonconvulsive status epilepticus is a commonly overlooked cause of altered mental s...

Bio-inspired deep learning-personalized ensemble Alzheimer's diagnosis model for mental well-being.

Most classification models for Alzheimer's Diagnosis (AD) do not have specific strategies for indivi...

Predictive modeling of ambulatory outcomes after spinal cord injury using machine learning.

STUDY DESIGN: Retrospective multi-site cohort study.

Association of Cardiovascular Health With Brain Age Estimated Using Machine Learning Methods in Middle-Aged and Older Adults.

BACKGROUND AND OBJECTIVES: Cardiovascular health (CVH) has been associated with cognitive decline an...

Insights into Parkinson's Disease-Related Freezing of Gait Detection and Prediction Approaches: A Meta Analysis.

Parkinson's Disease (PD) is a complex neurodegenerative disorder characterized by a spectrum of moto...

Classification of Visually Induced Motion Sickness Based on Phase-Locked Value Functional Connectivity Matrix and CNN-LSTM.

To effectively detect motion sickness induced by virtual reality environments, we developed a classi...

Machine learning analysis with population data for prepregnancy and perinatal risk factors for the neurodevelopmental delay of offspring.

Neurodevelopmental disorders (NDD) in offspring are associated with a complex combination of pre-and...

Large-scale foundation models and generative AI for BigData neuroscience.

Recent advances in machine learning have led to revolutionary breakthroughs in computer games, image...

Evolutionary Strategies AI Addresses Multiple Technical Challenges in Deep Learning Deployment: Proof-of-Principle Demonstration for Neuroblastoma Brain Metastasis Detection.

Two significant obstacles hinder the advancement of Radiology AI. The first is the challenge of over...

Classification of Parkinson's disease severity using gait stance signals in a spatiotemporal deep learning classifier.

Parkinson's disease (PD) is a degenerative nervous system disorder involving motor disturbances. Mot...

Deep Learning for hand tracking in Parkinson's Disease video-based assessment: Current and future perspectives.

BACKGROUND: Parkinson's Disease (PD) demands early diagnosis and frequent assessment of symptoms. In...

Study of machine learning techniques for outcome assessment of leptospirosis patients.

Leptospirosis is a global disease that impacts people worldwide, particularly in humid and tropical ...

An organic brain-inspired platform with neurotransmitter closed-loop control, actuation and reinforcement learning.

Organic neuromorphic platforms have recently received growing interest for the implementation and in...