Cardiovascular

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

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Detection of Right and Left Ventricular Dysfunction in Pediatric Patients Using Artificial Intelligence-Enabled ECGs.

BACKGROUND: Early detection of left and right ventricular systolic dysfunction (LVSD and RVSD respec...

Identification of novel hypertension biomarkers using explainable AI and metabolomics.

BACKGROUND: The global incidence of hypertension, a condition of elevated blood pressure, is rising ...

Multimodal AI/ML for discovering novel biomarkers and predicting disease using multi-omics profiles of patients with cardiovascular diseases.

Cardiovascular diseases (CVDs) are complex, multifactorial conditions that require personalized asse...

AI derived ECG global longitudinal strain compared to echocardiographic measurements.

Left ventricular (LV) global longitudinal strain (LVGLS) is versatile; however, it is difficult to o...

A Machine Learning-derived Risk Score Improves Prediction of Outcomes After LVAD Implantation: An Analysis of the INTERMACS Database.

BACKGROUND: Significant variability in outcomes after left ventricular assist device (LVAD) implanta...

Predictive performance of machine learning models for kidney complications following coronary interventions: a systematic review and meta-analysis.

BACKGROUND: Acute kidney injury (AKI) and contrast-induced nephropathy (CIN) are common complication...

ChatGPT Responses to Clinical Questions in the Japan Atherosclerosis Society Guidelines for Prevention of Atherosclerotic Cardiovascular Disease 2022.

AIMS: Artificial intelligence is increasingly used in the medical field. We assessed the accuracy an...

Artificial Intelligence-Based Fully Automated Quantitative Coronary Angiography vs Optical Coherence Tomography-Guided PCI: The FLASH Trial.

BACKGROUND: Recently developed artificial intelligence-based coronary angiography (AI-QCA, fully aut...

A cross-attention-based deep learning approach for predicting functional stroke outcomes using 4D CTP imaging and clinical metadata.

Acute ischemic stroke (AIS) remains a global health challenge, leading to long-term functional disab...

Metabolomics-Based Machine Learning for Predicting Mortality: Unveiling Multisystem Impacts on Health.

Reliable predictors of long-term all-cause mortality are needed for middle-aged and older population...

Estimating individual risk of catheter-associated urinary tract infections using explainable artificial intelligence on clinical data.

BACKGROUND: Catheter-associated urinary tract infections (CAUTIs) increase clinical burdens. Identif...

Artificial Intelligence Algorithms in Cardiovascular Medicine: An Attainable Promise to Improve Patient Outcomes or an Inaccessible Investment?

PURPOSE OF REVIEW: This opinion paper highlights the advancements in artificial intelligence (AI) te...

Brain Activation Pattern Caused by Soft Rehabilitation Glove and Virtual Reality Scenes: A Pilot fNIRS Study.

Clinical studies have proved significant improvements in hand motor function in stroke patients when...

SDS-Net: A Synchronized Dual-Stage Network for Predicting Patients Within 4.5-h Thrombolytic Treatment Window Using MRI.

Timely and precise identification of acute ischemic stroke (AIS) within 4.5 h is imperative for effe...

Post-Cardiac arrest outcome prediction using machine learning: A systematic review and meta-analysis.

BACKGROUND: Early and reliable prognostication in post-cardiac arrest patients remains challenging, ...

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