Cardiovascular

Acute Coronary Syndrome

Latest AI and machine learning research in acute coronary syndrome for healthcare professionals.

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Showing 232-252 of 6,674 articles
Elevated Plasma von Willebrand Factor Levels Are Associated With Subsequent Ischemic Stroke in Persons With Treated HIV Infection.

BACKGROUND: We assessed whether key biomarkers of endothelial activation and hemostasis/thrombosis w...

Explainable artificial intelligence for pharmacovigilance: What features are important when predicting adverse outcomes?

BACKGROUND AND OBJECTIVE: Explainable Artificial Intelligence (XAI) has been identified as a viable ...

Application of Artificial Intelligence in Acute Coronary Syndrome: A Brief Literature Review.

Artificial intelligence (AI) is defined as a set of algorithms and intelligence to try to imitate hu...

Machine learning risk prediction model for acute coronary syndrome and death from use of non-steroidal anti-inflammatory drugs in administrative data.

Our aim was to investigate the usefulness of machine learning approaches on linked administrative he...

Imputation of the continuous arterial line blood pressure waveform from non-invasive measurements using deep learning.

In two-thirds of intensive care unit (ICU) patients and 90% of surgical patients, arterial blood pre...

Short- and long-term mortality prediction after an acute ST-elevation myocardial infarction (STEMI) in Asians: A machine learning approach.

BACKGROUND: Conventional risk score for predicting short and long-term mortality following an ST-seg...

Robot-assisted Exploration of Somatic Nerves in the Pelvis and Transection of the Sacrospinous Ligament for Alcock Canal Syndrome.

STUDY OBJECTIVE: Some articles have reported the surgical management of Alcock canal syndrome (ACS) ...

Deep Semantic Segmentation Feature-Based Radiomics for the Classification Tasks in Medical Image Analysis.

Recently, an emerging trend in medical image classification is to combine radiomics framework with d...

Machine learning enhances the performance of short and long-term mortality prediction model in non-ST-segment elevation myocardial infarction.

Machine learning (ML) has been suggested to improve the performance of prediction models. Neverthele...

Prediction of venous thromboembolism with machine learning techniques in young-middle-aged inpatients.

Accumulating studies appear to suggest that the risk factors for venous thromboembolism (VTE) among ...

Systematic review of machine learning models for personalised dosing of heparin.

AIM: To identify and critically appraise studies of prediction models, developed using machine learn...

Deep learning for predicting COVID-19 malignant progression.

As COVID-19 is highly infectious, many patients can simultaneously flood into hospitals for diagnosi...

In Vitro Measurements of Shear-Mediated Platelet Adhesion Kinematics as Analyzed through Machine Learning.

Platelet adhesion to blood vessel walls in shear flow is essential to initiating the blood coagulati...

Risk stratification of ST-segment elevation myocardial infarction (STEMI) patients using machine learning based on lipid profiles.

BACKGROUND: Numerous studies have revealed the relationship between lipid expression and increased c...

Machine learning and deep learning to predict mortality in patients with spontaneous coronary artery dissection.

Machine learning (ML) and deep learning (DL) can successfully predict high prevalence events in very...

Robot-assisted transthoracic first rib resection for venous thoracic outlet syndrome.

BACKGROUND: Venous thoracic outlet syndrome (vTOS) is caused by external compression of the subclavi...

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