Neurology

Interpretable Cross-Modal Alignment Network for EEG Visual Decoding With Algorithm Unrolling.

Accurate decoding in electroencephalography (EEG) technology, particularly for rapid visual stimuli,...

Demographic Data Supporting FDA Authorization of AI Devices for Alzheimer Disease and Related Dementias.

Structural MRI-based Computer-aided Diagnosis Models for Alzheimer Disease: Insights into Misclassifications and Diagnostic Limitations.

Purpose To examine common patterns among different computer-aided diagnosis (CAD) models for Alzhei...

Electroencephalogram Features Distinguish Cases of Cerebral Malaria Among Malawian Children With Fever and Coma.

BACKGROUND: In febrile comatose patients living in malaria-endemic areas, overlapping symptoms and l...

Self-Spiking Linear Neuromorphic Soft Pressure Sensor for Underwater Sensing Applications.

Many aquatic vertebrates rely on neuromasts in their lateral line system to detect water vibrations ...

Radiomics, machine learning, and deep learning for hippocampal sclerosis identification: a systematic review and diagnostic meta-analysis.

PURPOSE: Hippocampal sclerosis (HS) is the primary pathological finding in temporal lobe epilepsy (T...

Association between long-term exposure of polystyrene microplastics and exacerbation of seizure symptoms: Evidence from multiple approaches.

Microplastics are tiny plastic particles originating from both commercial product manufacturing and ...

Integrated transcriptomic and proteomic analysis identifies FBXW7 as a key regulator of tau homeostasis in Alzheimer's disease.

BackgroundAlzheimer's disease (AD) is a progressive neurodegenerative disorder driven by complex, in...

Integrative transcriptomics and metabolomics reveal neuroendocrine-lipid crosstalk and adenosine signaling in broiler under heat stress.

BACKGROUND: Heat stress (HS) is a significant challenge in poultry, negatively impacting feed effici...

A hybrid filtering and deep learning approach for early Alzheimer's disease identification.

Alzheimer's disease is a progressive neurological disorder that profoundly affects cognitive functio...

Challenges in the Management of Stroke in Intensive Care Units in Low- and Middle-Income Countries.

Despite numerous advances in stroke care over the last decades, financial and structural barriers li...

Comparing non-machine learning vs. machine learning methods for Ki67 scoring in gastrointestinal neuroendocrine tumors.

The Ki67 score is a crucial prognostic biomarker for neuroendocrine tumors, but its manual assessmen...

A novel deep learning-based brain age prediction framework for routine clinical MRI scans.

Physiological brain aging is associated with cognitive impairment and neuroanatomical changes. Brain...

Enhancing EEG-Based Schizophrenia Diagnosis with Explainable Multi-Branch Deep Learning.

Schizophrenia poses diagnostic challenges due to a lack of objective assessment. We propose MBSzEEGN...

FedEMG: Achieving Generalization, Personalization, and Resource Efficiency in EMG-based Upper-Limb Rehabilitation through Federated Prototype Learning.

Upper extremity amputation, often necessitated by traumatic injuries, significantly impacts an indiv...

Proteomic Signatures of Epigenetic Age in African Green Monkey Cerebrospinal Fluid and Plasma.

Strategies to slow the aging process or mitigate its consequences on health rely on the validation o...

Necl-4/CADM4 regulates GABAergic synaptic strength on GABAergic inhibitory neurons via ErbB4 activation and prevents neuronal impairments.

Neural networks comprise excitatory and inhibitory neurons, linked through excitatory and inhibitory...

Candesartan Mitigates Perioperative Neurocognitive Disorders by Modulating Hypertension-Linked Neuroinflammatory Factor.

Perioperative neurocognitive disorders (PND) are linked to neuroinflammation, a key factor in hypert...

Brain Oscillations in Bipolar Disorder: Insights from Quantitative EEG Studies.

IntroductionQuantitative electroencephalography (QEEG) is a neurophysiological tool that analyzes br...

Early detection of Parkinson's disease: Machine learning-based prediction of UPDRS Part III scores in patients using smartphone assessments.

BackgroundDetecting motor symptoms in Parkinson's disease (PD) at home, especially in the prodromal,...

Prediction of early postoperative complications and transfusion risk after lumbar spinal stenosis surgery in geriatric patients: machine learning approach based on comprehensive geriatric assessment.

BACKGROUND: Lumbar spinal stenosis is one of the most common surgery-requiring conditions of the spi...