Strokes

Clinical History, Spirometry, and CT Features Can Predict Dyspnea in Smokers with and without Spirometry-Defined COPD.

Interpretable Machine Learning for Stroke Recovery: Predicting Discharge and 3-Month Functional Outcomes.

IntroductionStroke is a leading cause of disability worldwide. This study uses Machine Learning models to investigate factors influencing modified Rankin Scale scores at discharge and three months post-discharge.MethodsData from 116 stroke patients were analyzed using four predictive models: Logistic Regression, Support Vector Machine, Random Forest, and Extreme Gradient Boosting (XGB). Shapley Ad...

TrustNet: a lightweight network with integrated uncertainty quantification and quantitative explainable AI for ischemic stroke detection in CT images.

Bulk and single-cell transcriptomics for identification of potential diagnostic biomarkers associated with pulmonary arterial hypertension and integrated stress response and experimental validation.

BACKGROUND: Pulmonary arterial hypertension (PAH) is a lethal vascular disorder characterized by irreversible remodeling of the pulmonary arteries, bu...

Novel Systemic Associations of Idiopathic Epiretinal Membrane Identified via Machine Learning.

PURPOSE: To discover novel systemic associations that may lead to idiopathic epiretinal membrane (iERM) using interpretable machine learning models. D...

Prediction of hemorrhagic transformation after intravenous thrombolysis in acute anterior circulation ischemic stroke through radiomics-based machine learning models.

BACKGROUND: Hemorrhagic transformation (HT) and its associated neurological deterioration remain major concerns that limit decision-making in thrombol...

Influence of deep learning image reconstruction and adaptive statistical iterative reconstruction-V on automated Alberta stroke program early CT score- evaluation.

PURPOSE: The Alberta Stroke Program Early CT Score (ASPECTS) and advances in CT reconstruction play important roles in the neurodiagnostic workflow. T...

Endocrine hypertension in 2025: how AI and multiomics are revolutionizing detection.

INTRODUCTION: Endocrine hypertension (EH) represents a small yet clinically significant subset of secondary hypertension with curative potential. Rece...

Efficacy and neural mechanisms of a vibrotactile-enhanced, brain-controlled soft robotic glove for upper limb rehabilitation after stroke: a multicentre randomised controlled trial protocol.

INTRODUCTION: Soft robotic gloves (SRGs) integrated with brain-computer interfaces (BCIs) have demonstrated potential in facilitating motor recovery a...

AI- vs Human-Based Assessment of Medical Interview Transcripts in a Generative AI-Simulated Patient System: Cross-Sectional Validation Study.

BACKGROUND: Generative artificial intelligence (AI) is increasingly used in medical education, including AI-based virtual patients to improve intervie...

LeCoder: A large-scale automated coder for coding errors in word-production tasks.

Speech errors have been instrumental in advancing our understanding of the architecture of the language production system, the nature of its represent...

Prediction of Major Stroke (NIHSS > 5) Based on MR Perfusion Imaging Using a 3D ResNet.

PURPOSE: Prediction of stroke symptoms from perfusion patterns in ischemic stroke imaging would be desirable for decision making in relevant clinical ...

​Aging-related gene signatures as potential biomarkers in ischemic stroke: an integrated bioinformatics and machine learning study.

Application of machine learning approaches to develop predictive models for diabetes and hypertension among Bangladeshi Adults.

With rapid urbanization, lifestyle changes, and an aging population, non-communicable diseases (NCDs), including hypertension and diabetes, pose signi...

Machine learning for dysphagia risk prediction in older adults after acute ischemic stroke.

Development and validation of an explainable machine learning prediction model for futile recanalization after mechanical thrombectomy in acute large vessel occlusion stroke.

BACKGROUND: Mechanical thrombectomy (MT) is the primary treatment for acute ischemic stroke (AIS) caused by large vessel occlusion (LVO). However, the...

Proactive haemodynamic management using the hypotension prediction index during caesarean section: a randomised controlled study.

INTRODUCTION: Intra-operative hypotension is common during caesarean section and may result in adverse maternal effects, such as nausea and vomiting. ...

Marine-Derived bioactive compounds from Aquaculture: Receptor-Mediated neuroprotection in neurodegenerative disorders.

Neurodegenerative diseases, like Alzheimer's disease (AD), Parkinson's disease (PD), Huntington's disease (HD), amyotrophic lateral sclerosis (ALS), a...

Machine Learning-Assisted Detection of Phosgene and Acetyl Chloride via a Dual-Probe Fluorescent Platform with Differential Reactivity.

Phosgene and acyl chlorides are highly toxic chemicals that pose serious threats to human health and environmental safety, yet their rapid and reliabl...

The association between liver disease and stroke risk: A cross-sectional study with machine learning in a large-scale Chinese cohort.

INTRODUCTION: This study aimed to investigate the association between liver disease (LD) and stroke using cross-sectional data from the China Health a...