Cardiovascular

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 opt...

In silico prediction of drug-induced cardiotoxicity with ensemble machine learning and structural pattern recognition.

Drug-induced cardiotoxicity poses a significant risk to human health, and reliable predictive models...

Identification of individuals who benefit from omega-3 fatty acid supplementation to prevent coronary heart disease: a machine-learning analysis of the VITAL.

Randomized controlled trials (RCTs) have demonstrated benefits of marine omega-3 polyunsaturated fat...

A hybrid approach to heart disease prediction using a fractional-order mathematical model and machine learning algorithm.

Heart disease remains one of the leading causes of morbidity and mortality worldwide, necessitating ...

Epicardial adipose tissue, myocardial remodelling and adverse outcomes in asymptomatic aortic stenosis: a post hoc analysis of a randomised controlled trial.

BACKGROUND: Epicardial adipose tissue represents a metabolically active visceral fat depot that is i...

Machine learning prediction models for stroke-associated pneumonia:Meta-analysis.

OBJECTIVE: The heterogeneity of machine learning (ML) models predicting the risk of stroke-associate...

Efficacy of an Automated Pulmonary Embolism (PE) Detection Algorithm on Routine Contrast-Enhanced Chest CT Imaging for Non-PE Studies.

The urgency to accelerate PE management and minimize patient risk has driven the development of arti...

Challenges and opportunities in assessing right ventricular structure and function: a Roadmap for standardization, clinical implementation and research.

Given its crucial role in determining patient symptoms and outcomes in various cardiopulmonary disea...

Machine learning methods, applications and economic analysis to predict heart failure hospitalisation risk: a scoping review.

BACKGROUND:  Machine Learning (ML) has been transformative in healthcare, enabling more precise diag...

Safety of nonselective nonsteroidal anti-inflammatory drugs in cardiac surgery: a historical cohort study.

PURPOSE: Pain management after cardiac surgery is imperative, as inadequate analgesia can increase t...

Renal Dysfunction Across the Spectrum of Cardiogenic Shock: Mechanisms, Clinical Implications, and Therapeutic Strategies.

PURPOSE OF REVIEW: This review aims to elucidate the complex interplay between cardiogenic shock (CS...

Death One Hour After Terminal Extubation in Children: Validation of a Machine Learning Model to Predict Cardiac Death After Withdrawal of Life-Sustaining Treatment in a Multicenter Cohort, 2009-2021.

OBJECTIVES: In the PICU, predicting death within 1 hour after terminal extubation (TE) is valuable i...

Exploring the complex interplay between oral infection, periodontitis, and robust microRNA induction, including multiple known oncogenic miRNAs.

() is an oral commensal bacterium that can become pathogenic and is associated with periodontitis, ...

Letter by Sacoransky Regarding Article, "Deep Learning-Derived Cardiac Chamber Volumes and Mass From PET/CT Attenuation Scans: Associations With Myocardial Flow Reserve and Heart Failure".

Towards a dynamic model to estimate evolving risk of major bleeding after percutaneous coronary intervention.

While static risk models may identify key driving risk factors, the dynamic nature of risk requires ...

Personalized machine learning models for noninvasive hypoglycemia detection in people with type 1 diabetes using a smartwatch: Insights into feature importance during waking and sleeping times.

Hypoglycemia is a major challenge for people with diabetes. Therefore, glycemic monitoring is an imp...

Predictors of Length-of-Stay Among Transcatheter Aortic Valve Replacement Patients Using a Supervised Machine Learning Algorithm.

BACKGROUND: Length of stay following transcatheter aortic valve replacement (TAVR) continues to impr...

Generative adversarial network augmented data for improved heart sound abnormality detection.

The PhysioNet/Computing in Cardiology (CinC) Challenge 2016 dataset has driven significant advanceme...

Artificial Intelligence Powered Real-Time Coronary Stenosis Recognition and Quantification in Angiography.

Effective and automated measurement of coronary lesions is essential for timely decision-making duri...

A Comprehensive Framework for the Prediction of Intra-Operative Hypotension.

In this paper, the problem of triggering early warning for intra-operative hypotension (IOH) is addr...

Ultrasound Displacement Tracking Techniques for Post-Stroke Myofascial Shear Strain Quantification.

OBJECTIVE: Ultrasound shear strain is a potential biomarker of myofascial dysfunction. However, the ...