Neurology

Profiling of hypoxic and extracellular matrix remodeling markers in biofluids and cerebral tissue after traumatic brain injury: expression and signaling crosstalk of HIF-1α, MMP-9/14 and EPHA2.

Traumatic brain injury (TBI) remains a formidable clinical, neuropathological, and forensic challenge, constituting a leading cause of death as well a neuroscientific research target worldwide. A deeper understanding of the molecular signatures underlying vascular and extracellular matrix remodeling in TBI seems to be critical both for the development of diagnostic biomarkers in post-mortem neurop...

Corrigendum to: A Comprehensive Review on Deep Learning Techniques in Alzheimer's Disease Diagnosis.

In the originally published article entitled "A Comprehensive Review on Deep Learning Techniques in Alzheimer's Disease Diagnosis", published in "Current Topics in Medicinal Chemistry" Vol: 25 Issue: 04 [1], certain phrases and expressions were unclear, which may have affected readability. These have now been revised to improve clarity and ensure that the intended meaning is accurately conveyed. T...

Machine learning-based analysis of prognostic factors in patients with tuberculous meningitis.

Predicting self-image satisfaction after adult spinal deformity surgery: a machine learning approach using patient phenotypes.

PURPOSE: To characterize the evolution of the Self-Image (SI) domain of the Scoliosis Research Society-22 item questionnaire (SRS-22) in adult spinal ...

A dorsal versus ventral network for understanding others in the developing brain.

Young children strongly depend on others, and learning to understand their mental states (referred to as Theory of Mind, ToM) is a key challenge of ea...

Visualization of the Trochlear Nerve Using Deep Learning-enhanced 3D T2-weighted MR Imaging at 3T.

PURPOSE: Cranial nerve imaging with 3T MRI commonly uses 3D fast imaging employing steady-state acquisition (3D-FIESTA); however, this sequence has li...

Independent evaluation of deep learning models for detecting focal cortical dysplasia.

The purpose of this study is to perform an independent assessment of three state-of-the-art tools for the detection of focal cortical dysplasia (FCD) ...

An AI-based nomogram (the CGRP score) for the prediction of response to modern migraine therapies: an independent assessment and some considerations on the application of AI tools in clinical setting.

Past, present and future perspectives of traumatic brain injury.

Despite extensive research, traumatic brain injury (TBI) imposes significant mortality and morbidity burden globally. This narrative review provides a...

MAGCANet: A multiscale adaptive graph-convolutional attention network for MI-EEG decoding.

OBJECTIVE: Motor imagery EEG (MI-EEG) decoding remains challenging due to low signal-to-noise ratios and pronounced inter-subject variability. Althoug...

Development and Validation of a Machine Learning Model to Predict Oral Anticoagulant Use in Stroke From Prothrombin Time-International Normalized Ratio and Activated Partial Thromboplastin Time.

BACKGROUND: Timely recognition of oral anticoagulant use is critical in acute stroke but is often hampered by impaired consciousness and unavailable m...

Early cognitive screening for individuals on the dementia continuum: A novel approach amid current trends.

Mild cognitive impairment (MCI) is a critical transitional stage between normal aging and dementia that remains challenging to detect. Many traditiona...

Assessing Disorders of Consciousness Using Temporal Sleep Dynamics Extracted From Whole-Night PSG.

Accurate assessment of patients with disorders of consciousness (DoC) remains a major clinical challenge due to the limitations of behavior-based eval...

Financial Burden in Adults With Chronic Illness in Switzerland: A Secondary Analysis of Qualitative Interviews Using Natural Language Processing and Topic Modeling.

BACKGROUND: Chronic illness may cause a financial burden that affects patients, their caregivers, and families. While international research, mostly f...

Interrater Reliability of Electroencephalogram Interpretations in Febrile Comatose African Children: Implications for Automated Interpretation Algorithm Creation.

Electroencephalography (EEG) is a diagnostic and prognostic tool used worldwide in the clinical care of comatose patients. Scalability of EEG use in r...

An attention-based multimodal deep learning framework integrating EEG and ECG for enhanced stress detection.

Chronic stress is an important threat in Public Health, as it negatively impacts both the Body and Mind. Current methods for measuring and identifying...

Explainable artificial intelligence for early Alzheimer's diagnosis using enhanced grey relational features and multimodal data.

Alzheimer's disease, a progressive neurodegenerative disorder, presents a growing global health challenge due to its increasing prevalence and lack of...

Artificial intelligence in neurology practice: promise, perils, and a roadmap for responsible integration.

Artificial intelligence (AI) has emerged as a transformative force in neurology, offering unprecedented potential to enhance diagnostic precision, str...

Corticomorphic Hybrid CNN-SNN Architecture for EEG-Based Low-Footprint Low-Latency Auditory Attention Detection.

PURPOSE: In the context of a multi-speaker "cocktail party" scenario where listeners selectively focus on specific speakers, human auditory attention ...

High-Speed Instance Segmentation for Endoscopic Spine Surgery: Multicenter Validation and Inference Speed Evaluation.

Study DesignRetrospective Multicenter Cohort Study.ObjectivesTo develop and validate an AI-based high-speed multi-class instance segmentation system f...