Strokes

Enhancing upper limb motor recovery prediction after acute stroke using EEG and subacute data.

Electroencephalography (EEG) has shown promise in assessing and monitoring functional recovery in st...

MEF2A-mediated inhibition of ischemic stroke injury via the PI3K/AKT pathway: a comprehensive bioinformatics and in vitro study.

Explainable multi-modal approach for uncovering key predictors of stroke-risk from ECG, EMG, blood pressure, and respiratory signals.

Accurate and timely stroke-risk prediction is necessary to help patients at risk take guided measure...

Graph Convolutional Networks Enable Fast Hemorrhagic Stroke Monitoring With Electrical Impedance Tomography.

OBJECTIVE: To develop a fast image reconstruction method for stroke monitoring with electrical imped...

Prediction of mortality, bleeding, and ischaemic events in patients with cancer and acute coronary syndrome: a model development and validation study.

BACKGROUND: Accurate assessment of mortality, bleeding, and atherothrombotic risk in patients with c...

The Impact of a Neuroradiologist on the Report of a Real-World CT Perfusion Imaging Map Derived from Artificial Intelligence/Machine Learning-Driven Software.

BACKGROUND AND PURPOSE: According to the guideline, CT perfusion should be read and analyzed by usin...

Integrative transcriptomics, machine learning, and molecular docking reveal that nicotine exacerbates ischemic stroke: TLR4-dependent activation of NLRP3/caspase-1/GSDMD-mediated microglial pyroptosis.

OBJECTIVE: This study aimed to clarify the molecular mechanisms through which nicotine (Nic) aggrava...

Machine learning models for predicting futile recanalisation after endovascular treatment in patients with large core infarction.

BACKGROUND: Predicting futile recanalisation following endovascular treatment (EVT) in patients with...

Digital hypertension in 2024-2025: emerging evidence and future directions.

Recent advances in digital technology are remarkable, and they are driving profound transformations ...

Unbiased Characterization of Atrial Fibrillation Phenotypic Architecture Provides Insight Into Genetic Liability and Clinically Relevant Outcomes.

BACKGROUND: Atrial fibrillation (AF) is a common and clinically heterogeneous arrhythmia. Machine le...

Individualized Treatment in Distal and Medium Vessel Occlusion Stroke Using a Validated Explainable Counterfactual Treatment Estimation Model.

OBJECTIVE: The optimal treatment for distal medium vessel occlusion (DMVO) stroke remains uncertain,...

AI-driven low-cost rehabilitation exergame as a lightweight framework for stroke assessment.

Stroke is a leading cause of long-term disability, often affecting upper-limb motor function and req...

Mechanisms, precision therapies, and technological frontiers in coronary atherosclerosis: a comprehensive review.

Coronary atherosclerosis is a leading cause of morbidity and mortality worldwide and is characterize...

An integrative clinical and bioinformatic analysis identifies MicroRNAs as biomarkers of ischemic stroke severity.

Identifying reliable circulating biomarkers is crucial for improving the diagnosis and risk stratifi...

Recognizing the feature of knee hyperextension in stroke patients based on transformer-long-short-term memory model.

BACKGROUND: Recognizing knee hyperextension during gait in stroke patients is clinically challenging...

Machine learning-based LASSO-Cox model for dementia prediction: the role of midlife cardiometabolic, inflammatory, and genetic risk factors in a US cohort.

PURPOSE: We aimed to identify key midlife dementia predictors and develop a novel machine learning (...

Associations between contralesional neuroplasticity and motor impairment through deep learning-derived MRI regional brain age in chronic stroke (ENIGMA): a multicohort, retrospective, observational study.

BACKGROUND: Stroke leads to complex chronic structural and functional brain changes that specificall...

Artificial intelligence-based software to support mechanical thrombectomy transfer decision in low-volume primary stroke centers: a multicenter, retrospective study.

INTRODUCTION: To assess the potential benefit of artificial intelligence (AI) based imaging software...

Lung scintigraphy for the diagnosis of acute pulmonary embolism.

Pulmonary embolism (PE) remains a major diagnostic challenge due to its potentially life-threatening...

How do chronic diseases affect personal and household income? A double debiased machine learning analysis of the China health and retirement longitudinal study (CHARLS) in older adults.

OBJECTIVES: This study aimed to investigate the impacts of chronic diseases such as hypertension, dy...

Machine learning for predicting functional outcomes in acute ischemic stroke: insights from a nationwide stroke registry.

Accurately predicting the prognosis of patients with acute ischemic stroke at discharge remains high...