Strokes

Modulated smooth muscle cells accumulate late in human coronary atherosclerosis and are temporally and spatially linked to necrotic core formation

Proliferation of arterial smooth muscle cells (SMCs) and their modulation to alternative mesenchymal phenotypes is a central mechanism in the growth of atherosclerotic lesions. The underlying processes have been studied extensively in mouse models, but a detailed analysis of when and where modulated SMCs accumulate in human atherosclerosis is lacking. The present study mapped modulated SMC subtype...

Predicting mortality in critically ill patients with hypertension using machine learning and deep learning models

Accurate prediction of mortality in critically ill patients with hypertension admitted to the Intensive Care Unit (ICU) is essential for guiding clinical decision-making and improving patient outcomes. Traditional prognostic tools often fall short in capturing the complex interactions between clinical variables in this high-risk population. Recent advances in machine learning (ML) and deep learnin...

Finding the Clinical Traces of Cognitive Impairment in Patients with Heart Failure: A Natural Language Processing Study of Clinical Letters from Routine Care

Cognitive impairment is common in patients with heart failure, but to which extent cognitive complaints are evaluated and listed in clinical practice ...

Development and Application of Natural Language Processing on Unstructured Data in Hypertension: A Scoping Review

Hypertension is a global health concern with a vast body of unstructured data, such as clinical notes, diagnosis reports, and discharge summaries, tha...

Development of a Machine Learning Model for Predicting In-Hospital Mortality and Analyzing Associated Risk Factors Using Large Patient Samples

This study endeavors to construct a machine learning model to forecast in-hospital mortality and dissect associated risk factors, utilizing a vast dat...

Optimized Feature Selection and Advanced Machine Learning for Stroke Risk Prediction in Revascularized Coronary Artery Disease Patients

Coronary artery disease (CAD) is a leading cause of mortality, with stroke being a major complication following coronary revascularization procedures ...

Machine Learning for Predicting Thrombotic Recurrence in Antiphospholipid Syndrome

Thrombotic Antiphospholipid Syndrome (TAPS) is an autoimmune disorder associated with a high risk of recurrent thromboembolic events. Despite advances...

MRI-Derived Variables Combined with Machine Learning for Pulmonary Hypertension Risk Prediction: A Retrospective Analysis

Pulmonary hypertension (PH) is a severe and progressive vascular disease for which early diagnosis and risk stratification are critical for improving ...

Profile of deaths mentioning ischemic and hemorrhagic stroke in Brazil: a population-based machine learning analysis

Brazil has the highest stroke rates in Latin America. The aim of this study was to investigate the profile of deaths mentioning stroke in Brazil betwe...

Intraplaque haemorrhage quantification and molecular characterisation using attention based multiple instance learning

Intraplaque haemorrhage (IPH) represents a critical feature of plaque vulnerability as it is robustly associated with adverse cardiovascular events, i...

Predicting 28-Day Mortality in First-Time ICU Patients with Heart Failure and Hypertension Using LightGBM: A MIMIC-IV Study

Heart Failure (HF) and Hypertension (HTN) are common yet severe cardiovascular conditions, both of which significantly increase the risk of adverse ou...

Behavioral Clusters and Lesion Distributions in Ischemic Stroke, based on NIHSS Similarity Network

Stroke is a leading cause of death and disability. The subsequent dysfunctions relate to brain lesion location. The complex relationship between behav...

Artificial Intelligence for Short-Term Modified Rankin Score Prediction after Acute Stroke Symptoms Using Wrist-worn Triaxial Accelerometry Data

Functional outcomes after stroke are commonly assessed via modified Rankin Scale (mRS). However, mRS is subject to patient and assessor biases and is ...

Understanding the Feasibility of Computer Vision in Diagnosing Respiratory Infections in Pediatric Emergency Rooms

Respiratory infections are a leading cause of pediatric emergency visits globally, requiring timely and accurate assessment. This study evaluated the ...

Clinical phenotypes in hypertension: a data-driven approach to risk stratification and outcome prediction

Hypertension (HTN) is a major contributor to cardiovascular (CV) morbidity and mortality. Its heterogeneity complicates risk stratification. Unsupervi...

Development and accuracy of a novel machine learning model to detect toddlers’ physical activity and sedentary time using accelerometers: Little Movers Activity Analysis

Objective: (1) develop and test a novel, open-source, supervised machine learning model to detect toddlers’ physical activity (PA) and sedentary time ...

Machine Learning-Based Mortality Prediction in Critically Ill Patients with Hypertension: Comparative Analysis, Fairness, and Interpretability

Hypertension is a leading global health concern, significantly contributing to cardiovascular, cerebrovascular, and renal diseases. In critically ill ...

Extracting Carotid Stenosis Severity from Clinical Notes Using Natural Language Processing: Development, Validation, and Application in a Nationwide Veteran Cohort

Carotid stenosis, which is atherosclerotic narrowing of the extracranial carotid arteries, is an important risk factor for ischemic stroke. The preval...

DISCO: A Delta-NIHSS-Based Machine Learning Model for Predicting Recurrence, Disability, and Mortality Following Acute Ischemic Stroke

An accurate, robust, clinically accessible, and explainable predictive model for post-stroke composite outcomes could identify high-risk patients for ...

The allostatic overload in pregnancy during the COVID-19 pandemic and potential effects on the health of the mother-child dyad: Study Protocol

Allostatic load refers to the cumulative burden of stress and life events that involve the interaction of various physiological systems at differing l...