Neurology

An Advanced Deep Learning Framework for Ischemic and Hemorrhagic Brain Stroke Diagnosis Using Computed Tomography (CT) Images

Brain stroke is one of the leading causes of mortality and long-term disability worldwide, highlighting the need for precise and fast prediction techniques. Computed Tomography (CT) scan is considered one of the most effective methods for diagnosing brain strokes. The majority of stroke classification techniques rely on a single slice-level prediction mechanism, allowing the radiologist to manua...

Outcome prediction and individualized treatment effect estimation in patients with large vessel occlusion stroke

Mechanical thrombectomy has become the standard of care in patients with stroke due to large vessel occlusion (LVO). However, only 50% of successfully treated patients show a favorable outcome. We developed and evaluated interpretable deep learning models to predict functional outcomes in terms of the modified Rankin Scale score alongside individualized treatment effects (ITEs) using data of 449...

Intelligent Histology for Tumor Neurosurgery

The importance of rapid and accurate histologic analysis of surgical tissue in the operating room has been recognized for over a century. Our standa...

A Dopamine-Serotonin Theory of Consciousness

This work presents a comprehensive theory of consciousness grounded in mathematical formalism and supported by clinical data analysis. The framework...

Deep learning on high-density EEG during a cognitive task distinguishes patients with Parkinson's disease from healthy controls.

Parkinson's disease (PD) is a neurodegenerative disorder characterized by motor and non-motor symptoms, including cognitive impairment. Its diagnosis,...

Annotating neurophysiologic data at scale with optimized human input.

Neuroscience experiments and devices are generating unprecedented volumes of data, but analyzing and validating them presents practical challenges, pa...

Robust brain age estimation from structural MRI with contrastive learning

Estimating brain age from structural MRI has emerged as a powerful tool for characterizing normative and pathological aging. In this work, we explor...

Calibrated Self-supervised Vision Transformers Improve Intracranial Arterial Calcification Segmentation from Clinical CT Head Scans

Vision Transformers (ViTs) have gained significant popularity in the natural image domain but have been less successful in 3D medical image segmenta...

Beyond Black-Box AI: Interpretable Hybrid Systems for Dementia Care

The recent boom of large language models (LLMs) has re-ignited the hope that artificial intelligence (AI) systems could aid medical diagnosis. Yet d...

Geometry of orofacial neuromuscular signals: speech articulation decoding using surface electromyography.

In this article, we present data and methods for decoding speech articulations using surface electromyogram (EMG) signals. EMG-based speech neuroprost...

Customizable ROI-Based Deep Image Compression

Region of Interest (ROI)-based image compression optimizes bit allocation by prioritizing ROI for higher-quality reconstruction. However, as the use...

How I Do It: Three-Dimensional MR Neurography and Zero Echo Time MRI for Rendering of Peripheral Nerve and Bone.

MR neurography sequences provide excellent nerve-to-background soft tissue contrast, whereas a zero echo time (ZTE) MRI sequence provides cortical bon...

Does alignment alone predict mechanical complications after adult spinal deformity surgery? A machine learning comparison of alignment, bone quality, and soft tissue.

OBJECTIVE: Mechanical complications are a vexing occurrence after adult spinal deformity (ASD) surgery. While achieving ideal spinal alignment in ASD ...

Zero-shot segmentation of spinal vertebrae with metastatic lesions: an analysis of Meta's Segment Anything Model 2 and factors affecting learning free segmentation.

OBJECTIVE: Accurate vertebral segmentation is an important step in imaging analysis pipelines for diagnosis and subsequent treatment of spinal metasta...

Differential dementia detection from multimodal brain images in a real-world dataset.

INTRODUCTION: Artificial intelligence (AI) models have been applied to differential dementia detection tasks in brain images from curated, high-qualit...

Towards Investigating Residual Hearing Loss: Quantification of Fibrosis in a Novel Cochlear OCT Dataset.

OBJECTIVE: Cochlear implants (CIs) are bionic prostheses that restores hearing via electrical stimulation of the auditory nerve. Hybrid CIs, which use...

Volumetric and Diffusion Tensor Imaging Abnormalities Are Associated With Behavioral Changes Post-Concussion in a Youth Pig Model of Mild Traumatic Brain Injury.

Mild traumatic brain injury (mTBI) caused by sports-related incidents in children and youth often leads to prolonged cognitive impairments but remains...

Production of the Neurotoxin BMAA by Marine Diatoms Drives Its Widespread Occurrence in Estuarine and Coastal Ecosystems.

Phytoplankton are the primary producers of marine neurotoxins such as β--methylamino-l-alanine (BMAA), which cause seafood poisoning outbreaks in estu...

Non-traditional socio-environmental and geospatial determinants of Alzheimer's disease-related dementia mortality.

IMPORTANCE: Recent data point to the impact of non-traditional environmental and social factors on Alzheimer's Disease-Related Dementias (ADRD) mortal...

Unravelling the brain resilience following stroke: From injury to rewiring of the brain through pathway activation, drug targets, and therapeutic interventions.

Synaptic plasticity is a neuron's intrinsic ability to make new connections throughout life. The morphology and function of synapses are highly suscep...