Neurology

Co-simulation framework combining a microscopically detailed point neuron model of the hippocampal CA1 region with the macroscopic high-resolution virtual brain model.

The human brain is a complex adaptive system characterized by dynamic processes operating across multiple spatio-temporal scales. Capturing these dynamics requires computational models that can integrate different levels of resolution. In this work we present a multiscale co-simulation framework that couples whole-brain modeling with a detailed point-neuron model of the human hippocampal CA1 regio...

Beyond Subject-Specific Models in Dynamical Human-Machine Interaction: Benchmarking and Optimization Strategies.

Continuous finger position estimation from surface electromyography (EMG) enables smoother, more intuitive control in human-machine interfaces than discrete gesture classification. Accurate regression, however, requires effective temporal modeling and adaptation to user variability. We benchmark recurrent neural networks, temporal convolutional networks (TCNs), Transformers, and, for the first tim...

Multimodal Machine Learning and Deep Learning Approaches for Parkinson's Disease Diagnosis: A Comprehensive Survey.

Parkinson's disease (PD) is a progressive neurodegenerative disorder that profoundly affects patients' quality of life. Early and accurate diagnosis i...

Cardiorespiratory Markers of Type 2 Diabetes: Machine Learning-Based Analysis.

BACKGROUND: The global prevalence of type 2 diabetes mellitus (T2DM) poses significant challenges due to its association with increased cardiovascular...

AI and Wearables for Early Detection of Cognitive Impairment and Dementia: Systematic Review.

BACKGROUND: Traditional cognitive screening relies on episodic clinical assessments and may miss early changes preceding cognitive impairment and deme...

Real-time intraoperative confocal laser endomicroscopy with on-site neuropathologist consultation for glioma margin assessment: illustrative case.

BACKGROUND: Achieving maximal safe resection in glioma surgery requires accurate real-time margin assessment, yet existing technologies have limitatio...

Vocal biomarkers for geriatric health assessment: a scoping review protocol.

INTRODUCTION: Global ageing populations require accessible, non-invasive tools for early detection and monitoring of neurological chronic and neurodeg...

AI-Based STroke Risk fActor Classification and Treatment (ABSTRACT) study.

BACKGROUND: Stroke is a leading cause of death and disability worldwide, costing the UK approximately £26 billion annually. While lifestyle modificati...

Association of allostatic load index with cognitive impairment in high-risk stroke populations.

BACKGROUND: Chronic psychosocial stress induces cumulative physiological dysregulation that accelerates biological aging and contributes to the develo...

Trustworthy AI for medical decisions: Adversarially robust and fair machine learning prediction for Parkinson's disease.

Parkinson's disease (PD) is a neurodegenerative disorder characterized by motor and non-motor symptoms, including tremor, rigidity, and postural insta...

Gradient magnitude-based texture feature of the entorhinal cortex as a biomarker for Alzheimer's disease.

Volumetric analysis of brain structures is widely used to detect pathological changes in Alzheimer's disease (AD), but it has limited sensitivity to s...

Artificial Intelligence-Based Analysis of Central Nervous System Vasculopathy in Pediatric Sickle Cell Anemia.

In children with sickle cell anemia (SCA), central nervous system (CNS) complications such as chronic vasculopathy, silent cerebral infarcts, and over...

Comparative Analysis of Deep Learning Techniques in Alzheimer's Disease Diagnosis: Trends, Challenges, and Future Directions.

Alzheimer's disease is a slow, progressive neurological disorder that impacts the brain tissue and causes cells to die, the most common reason for dem...

Parietal repetitive transcranial magnetic stimulation enhances functional connectivity in patients with minimally conscious state.

The basis of disorders of consciousness is the destruction of brain functional connectivity, and the restoration of damaged connectivity is considered...

Cerebrovascular 5D flow MRI.

BACKGROUND: 4D flow MRI facilitates quantification of cardiac phase-resolved blood velocity vector fields and has successfully been deployed to study ...

Multiple screen addiction and neurological complaints in adolescents: A machine learning-based classification model.

INTRODUCTION: Multiple screen addiction is a growing public health problem, especially among young people. Early detection and classification of scree...

Features of B-mode ultrasound and contrast-enhanced ultrasound of carotid plaque based on deep learning enhance the prediction of vulnerable plaques associated with acute ischemic stroke.

OBJECTIVES: To develop an AI model using ultrasound features of carotid plaque for predicting the risk of acute ischemic stroke (AIS) and assess its e...

Performance of AI vs radiology residents in the detection of intracranial hemorrhage on emergency CT: a real-world analysis.

OBJECTIVE: To evaluate the performance of a commercial artificial intelligence (AI) software in detecting intracranial hemorrhage (ICH) in emergency s...

Subtypes of newly diagnosed type 2 diabetes and risk of complications: analysis of electronic health records in the USA.

AIMS/HYPOTHESIS: Data-driven subtyping of type 2 diabetes has not been translated into clinical practice due to the lack of routine fasting glucose an...

Unraveling the role of polyamine metabolism in postoperative delirium: insights into biochemical mechanisms and biomarker potential.

Postoperative delirium (POD) is a common complication in older surgical patients, linked to long-term cognitive decline and progression to dementia, y...