Neurology

Intelligent decision-making systems for early detection of alzheimer's disease using wearable technologies and deep learning.

Intelligent decision-making systems using wearable electronics and deep learning (DL) might identify Alzheimer's disease (AD) early for treatment. These technologies can continually monitor vital signs and behavioral characteristics to identify early cognitive deterioration in patients. Clinical examinations, neuroimaging, and cognitive testing are the main ways to identify Alzheimer's, but they a...

Machine learning-enabled prediction of hemorrhagic transformation post-thrombectomy using quantitative DSA.

This study aims to construct a predictive model for post-thrombectomy hemorrhagic transformation (HT) by integrating hemodynamic features derived from quantitative DSA (qDSA) with machine learning models. A retrospective analysis was conducted on patients with acute anterior circulation large-vessel occlusion who underwent MT at our center from January to December 2024. Immediate postoperative ant...

Increased cervical spinal cord signal intensity corresponds to specific cerebellar and cerebral functional changes in degenerative cervical myelopathy patients.

Increased signal intensity (ISI) on T2-weighted cervical MR is common in patients with degenerative cervical myelopathy (DCM). However, the subtype-sp...

Multi-organoid loop cerebral connectoids exhibit enhanced neuronal network dynamics and sequence-specific entrainment.

Reconstructing networks of neurons in vitro is essential for advancing our understanding of functional mechanisms and disease pathogenesis. However, n...

Personalized supervised and unsupervised intracranial sleep decoding during deep brain stimulation.

Impaired sleep in Parkinson's Disease (PD) is a significant unmet need. Targeting sleep stage-specific neurophysiologies with adaptive Deep Brain Stim...

Detecting cognitive impairment and psychological well-being among older adults.

The aging society urgently requires scalable methods to monitor cognitive decline and identify social and psychological factors indicative of dementia...

ClathPLM: Deep multi-view feature extraction with CNN and attention enhances clathrin protein identification.

Clathrin is a key structural protein in intracellular vesicle transport, mainly mediating clathrin-mediated endocytosis (CME) through trimeric assembl...

The association of environmental exposure with multiple sclerosis severity score: A study based on sequential data modeling.

Introduction Multiple Sclerosis (MS) is a chronic neuroinflammatory disease influenced by clinical, demographic, and environmental factors. Predicting...

Early diagnosis of Alzheimer's disease from functional rs-fMRI images based on deep learning networks and transfer learning approach.

Exploiting deep learning methods to accelerate the analysis of medical images and the interpretation of pathology results for early diagnosis of Alzhe...

Advances on the application of the Human Brainnetome Atlas in obsessive-compulsive disorder.

Obsessive-compulsive disorder (OCD) is a chronic psychiatric disorder characterized by persistent intrusive thoughts and repetitive behaviors, signifi...

Generative Artificial Intelligence-Enabled Saliency Analysis of Eye Tracking in Cerebral/Cortical Visual Impairment (SET-CVI).

PURPOSE: Children with cerebral/cortical visual impairment (CVI) have neurological conditions that impact visual pathways in the brain, leading to def...

Deep learning architectures for modeling and forecasting stroke cases in Ghana.

INTRODUCTION: Stroke remains a leading cause of global morbidity and mortality, ranking second in deaths and third in disability-adjusted life years (...

Spatial and spatiotemporal pattern of stroke relative risk in Ghana using Bayesian modelling approach.

INTRODUCTION: Stroke ranks as the second-leading cause of death and third in combined death and disability globally. In Ghana, there is a significant ...

Localization of the Berger effect in human posterior brain regions with simultaneous electroencephalogram (EEG) and stereo-EEG (SEEG) recordings.

The Berger effect, characterized by a marked increase in alpha power (8-13 Hz) upon eye closure, is a fundamental neurophysiological phenomenon whose ...

The Contribution of the Locus Ceruleus-Norepinephrine System to the Coupling between Pupil-Linked Arousal and Cortical State.

Understanding how pupil-linked arousal couples with cortical state is crucial for uncovering the neural mechanisms underlying brain state-dependent co...

An integrative multiomics random forest framework for robust biomarker discovery.

BACKGROUND: High-throughput technologies now produce a wide array of omics data, from genomic and transcriptomic profiles to epigenomic and proteomic ...

[Artificial intelligence in spinal surgery: current applications and future perspectives].

BACKGROUND: Spinal surgery is a highly complex field increasingly shaped by digital innovation. Artificial intelligence (AI) and machine learning (ML)...

STF: A Unified Framework for Joint Pixel-Level Segmentation and Tracking of Tissues in Endoscopic Surgery.

Endoscopic minimally invasive surgery relies on precise tissue video segmentation to avoid complications such as vascular bleeding or nerve injury. Ho...

Large Language Models Improve Scene Invariant Detection of Behaviours of Risk in Dementia Residential Care Across Multiple Surveillance Camera Views.

Behavioural and psychological symptoms of dementia pose challenges to the safety and well-being of individuals in residential care. The integration of...

Machine Learning-Driven Approach to Identify Freezing of Gait in Individuals with Parkinson's Disease Using Conventional Structural MRI and Clinical Measures.

BACKGROUND AND PURPOSE: Freezing of gait (FOG) presents a significant challenge in the management of Parkinson's disease (PD). Our study explored the ...