Cardiovascular

Strokes

Latest AI and machine learning research in strokes for healthcare professionals.

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Early Predictive Accuracy of Machine Learning for Hemorrhagic Transformation in Acute Ischemic Stroke: Systematic Review and Meta-Analysis.

BACKGROUND: Hemorrhagic transformation (HT) is commonly detected in acute ischemic stroke (AIS) and ...

Natural AlO Nanodielectric-Based Flexible Sensor with Triple Insensitivity for Healthcare and Robotics.

Flexible pressure sensors are critical for advanced systems such as electronic skins and human-machi...

Detection of carotid artery calcifications using artificial intelligence in dental radiographs: a systematic review and meta-analysis.

BACKGROUND: Carotid artery calcifications are important markers of cardiovascular health, often asso...

Long Short-Term Memory Network for Accelerometer-Based Hypertension Classification.

This study investigates the application of a Long Short-Term Memory (LSTM) architecture for classify...

Interpretable Independent Recurrent Networks for Forecasting Stroke in Atrial Fibrillation.

BACKGROUND: Atrial fibrillation (AF) is a major risk factor for transient ischemic attack (TIA)/isch...

Automated Risk Prediction of Post-Stroke Adverse Mental Outcomes Using Deep Learning Methods and Sequential Data.

Depression and anxiety are common comorbidities of stroke. Research has shown that about 30% of stro...

Electromechanical-assisted training for walking after stroke.

RATIONALE: Walking difficulties are common after a stroke. During rehabilitation, electromechanical ...

Deep learning for cerebral vascular occlusion segmentation: A novel ConvNeXtV2 and GRN-integrated U-Net framework for diffusion-weighted imaging.

Cerebral vascular occlusion is a serious condition that can lead to stroke and permanent neurologica...

Personalized Nutrition Strategies for Patients in the Intensive Care Unit: A Narrative Review on the Future of Critical Care Nutrition.

Critically ill patients in intensive care units (ICUs) are at high risk of malnutrition, which can ...

A deep learning and molecular modeling approach to repurposing Cangrelor as a potential inhibitor of Nipah virus.

Deforestation, urbanization, and climate change have significantly increased the risk of zoonotic di...

[Pulmonary vascular interventions: innovating through adaptation and advancing through differentiation].

Pulmonary vascular intervention technology, with its minimally invasive and precise advantages, has ...

A Clinical Neuroimaging Platform for Rapid, Automated Lesion Detection and Personalized Post-Stroke Outcome Prediction.

Predicting long-term functional outcomes for individuals with stroke is a significant challenge. Sol...

Neural pathways underlying the production of pitch and rhythm in aphasia.

Singing is a universal human attribute. Previous studies suggest that the ability to produce words t...

Lipid nanoparticle (LNP) mediated mRNA delivery in neurodegenerative diseases.

Neurodegenerative diseases (NDD) are characterized by the progressive loss of neurons and the impair...

Usability testing a web application to support evidence-based commissioning decisions for implementing mobile stroke units.

Commissioning of innovations in healthcare is a complex socio-technical process, ideally informed by...

Machine learning-based prediction of 90-day prognosis and in-hospital mortality in hemorrhagic stroke patients.

This study aims to predict hemorrhagic stroke outcomes, including 90-day prognosis and in-hospital m...

Lipid Ratios for Diagnosis and Prognosis of Pulmonary Hypertension.

RATIONALE: Pulmonary hypertension (PH) poses a significant health threat. Current biomarkers for PH ...

Prediction of the functional outcome of intensive inpatient rehabilitation after stroke using machine learning methods.

An accurate and reliable functional prognosis is vital to stroke patients addressing rehabilitation,...

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