Strokes

Artificial Intelligence-Enhanced Electrocardiography for Prediction of Occult Atrial Fibrillation in Patients With Stroke Who Undergo Prolonged Cardiac Monitoring.

OBJECTIVE: To evaluate the performance of an artificial intelligence (AI)-enhanced electrocardiography (ECG; AI-ECG) algorithm to predict atrial fibrillation (AF) detection on prolonged cardiac monitoring (PCM) after index stroke.

Identifying predictors and assessing causal effect on hypertension risk among adults using Double Machine Learning models: Insights from Bangladesh Demographic and Health Survey.

BACKGROUND: Hypertension poses a significant public health challenge in low- and middle-income countries. In Bangladesh, the Health Population and Nutrition Sector Development Program has shown effectiveness in resource-limited settings. Estimating causal relationships on hypertension while adjusting for nonlinear observed confounders in adult population is complex. This study aims to identify pre...

Multimodal nomogram integrating deep learning radiomics and hemodynamic parameters for early prediction of post-craniotomy intracranial hypertension.

To evaluate the effectiveness of deep learning radiomics nomogram in distinguishing early intracranial hypertension (IH) following primary decompressi...

Optimization for threat classification of various data types-based on ML model and LLM.

With the development of AI technology, the number of cyber security threats that exploit it is increasing rapidly, and it is urgent to build an effect...

Machine Learning simulations reveal oxygen's phase diagram and thermal properties at conditions relevant to white dwarfs.

Current studies show that oxygen does not aggregate into a polymeric phase even under pressures up to 10 TPa. To address the critical knowledge gap in...

A modified generative adversarial networks method for assisting the diagnosis of deep venous thrombosis complications in stroke patients.

Discriminate deep vein thrombosis, one of the complications in early stroke patients, in order to assist in diagnosis. We have constructed a new metho...

Automatic melanoma detection using an optimized five-stream convolutional neural network.

Melanoma is among the deadliest forms of malignant skin cancer, with the number of cases increasing dramatically worldwide. Its early and accurate dia...

Machine learning and transformer models for prediction of postoperative pneumonia risk in patients with lower limb fractures.

Postoperative pneumonia, a prevalent complication arising from lower limb fracture surgery, can significantly prolong hospitalization periods and elev...

Metabolomic biomarkers could be molecular clocks in timing stroke onset.

The preferred treatment for acute ischaemic stroke (AIS) is intravenous thrombolysis (IVT) administered within 4.5 hours (h) of symptom onset. This st...

Artificial Intelligence-Based Detection of Central Retinal Artery Occlusion Within 4.5 Hours on Standard Fundus Photographs.

BACKGROUND: Prompt diagnosis of acute central retinal artery occlusion (CRAO) is crucial for therapeutic management and stroke prevention. However, mo...

Predicting Retinal Nerve Fiber Layer Thickness From Ocular Hypertension Treatment Study Optic Disc Photographs.

IMPORTANCE: Deep learning predictions of retinal nerve fiber layer (RNFL) thickness derived from optic disc photographs may help to determine risk for...

From "time is brain" to "time is collaterals": updates on the role of cerebral collateral circulation in stroke.

BACKGROUND: Acute ischemic stroke (AIS) remains the leading cause of mortality and disability worldwide. While revascularization therapies-such as int...

Emergency radiology: roadmap for radiology departments.

Emergency radiology has evolved into a significant subspecialty over the past 2 decades, facing unique challenges including escalating imaging volumes...

Exploring the potential biomarkers between stroke and obstructive sleep apnea by WGCNA and machine learning.

BACKGROUND: Ischemic stroke (IS) and obstructive sleep apnea (OSA) are highly prevalent disorders with significant societal and individual burdens. OS...

Disease entity impacts muscle wasting in the ICU with COVID-19 patients losing muscle nearly twice as fast.

Muscle loss in critically ill patients, particularly during prolonged ICU stays, poses significant challenges to recovery and long-term outcomes. ICU-...

Prevalence and determinants of hypertension among adults of reproductive age in Tanzania: analysis of a cross-sectional Demographic and Health Survey.

OBJECTIVE: We aimed to estimate prevalence and identify determinants of hypertension in adults aged 15-49 years in Tanzania.

Neural mechanisms underlying the improvement of gait disturbances in stroke patients through robot-assisted gait training based on QEEG and fNIRS: a randomized controlled study.

BACKGROUND: Robot-assisted gait training is more effective in improving lower limb function and walking ability in stroke patients compared to convent...

Predicting pulmonary hemodynamics in pediatric pulmonary arterial hypertension using cardiac magnetic resonance imaging and machine learning: an exploratory pilot study.

PURPOSE: Pulmonary arterial hypertension (PAH) significantly affects the pulmonary vasculature, requiring accurate estimation of mean pulmonary arteri...

Optimizing stroke detection with genetic algorithm-based feature selection in deep learning models.

Brain stroke is a leading cause of disability and mortality worldwide, necessitating the development of accurate and efficient diagnostic models. In t...

Towards Artificial Intelligence-based Decision Support for Large-scale Screening for Atrial Fibrillation.

Atrial fibrillation is a prevalent cardiac arrhythmia, significantly increasing the risk of stroke, heart failure, and mortality. Early detection, esp...