Cardiovascular

Atherosclerosis

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

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A systematic review on deep learning-enabled coronary CT angiography for plaque and stenosis quantification and cardiac risk prediction.

BACKGROUND: Coronary artery disease (CAD) is a major worldwide health concern, contributing signific...

A digital photography dataset for Vaccinia Virus plaque quantification using Deep Learning.

Virological plaque assay is the major method of detecting and quantifying infectious viruses in rese...

Retinal Ischemic Perivascular Lesions (RIPLs) as Potential Biomarkers for Systemic Vascular Diseases: A Narrative Review of the Literature.

Retinal ischemic perivascular lesions (RIPLs) are characteristic focal thinning of the inner nuclear...

Application and optimization of the U-Net++ model for cerebral artery segmentation based on computed tomographic angiography images.

Accurate segmentation of cerebral arteries on computed tomography angiography (CTA) images is essent...

Predicting outcomes following open abdominal aortic aneurysm repair using machine learning.

Patients undergoing open surgical repair of abdominal aortic aneurysm (AAA) have a high risk of post...

IDENTIFYING A SEPSIS SUBPHENOTYPE CHARACTERIZED BY DYSREGULATED LIPOPROTEIN METABOLISM USING A SIMPLIFIED CLINICAL DATA ALGORITHM.

Background: Cholesterol metabolism is dysregulated in sepsis contributing to patient heterogeneity. ...

Plaque burden improves the detection of ischemic CAD over stenosis from coronary computed tomography angiography.

In symptomatic patients undergoing coronary CTA for suspected coronary artery disease (CAD), we asse...

MM-UKAN++: A Novel Kolmogorov-Arnold Network-Based U-Shaped Network for Ultrasound Image Segmentation.

Ultrasound (US) imaging is an important and commonly used medical imaging modality. Accurate and fas...

Transfer learning of multicellular organization via single-cell and spatial transcriptomics.

Biological tissues exhibit complex gene expression and multicellular patterns that are valuable to d...

Unsupervised machine learning analysis of optical coherence tomography radiomics features for predicting treatment outcomes in diabetic macular edema.

This study aimed to identify distinct clusters of diabetic macular edema (DME) patients with differe...

Identification of key therapeutic targets in nicotine-induced intracranial aneurysm through integrated bioinformatics and machine learning approaches.

BACKGROUND: Intracranial aneurysm (IA) is a critical cerebrovascular condition, and nicotine exposur...

Machine Learning-Based Prediction of Unplanned Readmission Due to Major Adverse Cardiac Events Among Hospitalized Patients with Blood Cancers.

BackgroundHospitalized patients with blood cancer face an elevated risk for cardiovascular diseases ...

Predicting Intraoperative Burst Suppression Using Preoperative EEG and Patient Characteristics.

Burst suppression (BS) is an electroencephalogram (EEG) pattern observed in patients undergoing gene...

Investigating long-term risk of aortic aneurysm and dissection from fluoroquinolones and the key contributing factors using machine learning methods.

The connection between fluoroquinolones and severe heart conditions, such as aortic aneurysm (AA) an...

Artificial intelligence-based machine learning protocols enable quicker assessment of aortic biomechanics: A case study.

Analyzing aortic biomechanical wall stresses for abdominal aortic aneurysms remains challenging. Cli...

Artificial Intelligence in CT Angiography for the Detection of Coronary Artery Stenosis and Calcified Plaque: A Systematic Review and Meta-analysis.

PURPOSE: We aimed to evaluate the diagnostic performance of artificial intelligence (AI) in detectin...

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