Cardiovascular

Responsible AI for cardiovascular disease detection: Towards a privacy-preserving and interpretable model.

BACKGROUND AND OBJECTIVE: Cardiovascular disease (CD) is a major global health concern, affecting mi...

Super-resolution deep-learning reconstruction for cardiac CT: impact of radiation dose and focal spot size on task-based image quality.

This study aimed to evaluate the impact of radiation dose and focal spot size on the image quality o...

CACSNet for automatic robust classification and segmentation of carotid artery calcification on panoramic radiographs using a cascaded deep learning network.

Stroke is one of the major causes of death worldwide, and is closely associated with atherosclerosis...

Machine-learning clustering analysis identifies novel phenogroups in patients with ST-elevation acute myocardial infarction.

BACKGROUND: Machine learning clustering of patients with ST-elevation acute myocardial infarction (S...

Microscopy Image Dataset for Deep Learning-Based Quantitative Assessment of Pulmonary Vascular Changes.

Pulmonary hypertension (PH) is a syndrome complex that accompanies a number of diseases of different...

Machine learning predictions of the adverse events of different treatments in patients with ischemic left ventricular systolic dysfunction.

This study aimed to develop several new machine learning models based on hibernating myocardium to p...

Systematic Review and Meta-Analysis of Prehospital Machine Learning Scores as Screening Tools for Early Detection of Large Vessel Occlusion in Patients With Suspected Stroke.

BACKGROUND: Enhanced detection of large vessel occlusion (LVO) through machine learning (ML) for acu...

Machine Learning Algorithms for Processing and Classifying Unsegmented Phonocardiographic Signals: An Efficient Edge Computing Solution Suitable for Wearable Devices.

The phonocardiogram (PCG) can be used as an affordable way to monitor heart conditions. This study p...

Risk prediction of cholangitis after stent implantation based on machine learning.

The risk of cholangitis after ERCP implantation in malignant obstructive jaundice patients remains u...

Identification of diabetic retinopathy classification using machine learning algorithms on clinical data and optical coherence tomography angiography.

BACKGROUND: To apply machine learning (ML) algorithms to perform multiclass diabetic retinopathy (DR...

Artificial intelligence-based automatic nidus segmentation of cerebral arteriovenous malformation on time-of-flight magnetic resonance angiography.

OBJECTIVE: Accurate nidus segmentation and quantification have long been challenging but important t...

Estimation of invasive coronary perfusion pressure using electrocardiogram and Photoplethysmography in a porcine model of cardiac arrest.

BACKGROUND: Coronary perfusion pressure (CPP) indicates spontaneous return of circulation and is rec...

Upper Limb Robots for Recovery of Motor Arm Function in Patients With Stroke: A Systematic Review and Meta-Analysis.

BACKGROUND AND OBJECTIVES: Robot technology to support upper limb (UL) rehabilitation poststroke has...

Learning From Extracorporeal Membrane Oxygenation Experience in Cardiac Arrest: Strengths and Limitations of Prognostic Modeling Using Machine Learning.

A real-world pharmacovigilance study on cardiovascular adverse events of tisagenlecleucel using machine learning approach.

Chimeric antigen receptor T-cell (CAR-T) therapies are a paradigm-shifting therapeutic in patients w...

Deep learning based ECG segmentation for delineation of diverse arrhythmias.

Accurate delineation of key waveforms in an ECG is a critical step in extracting relevant features t...

Streamlining Acute Abdominal Aortic Dissection Management-An AI-based CT Imaging Workflow.

Life-threatening acute aortic dissection (AD) demands timely diagnosis for effective intervention. T...

Cardiogenic Shock Update: New Trials, Evolving Management Paradigms, and Artificial Intelligence.

Machine-learning-based models assist the prediction of pulmonary embolism in autoimmune diseases: A retrospective, multicenter study.

BACKGROUND: Pulmonary embolism (PE) is a severe and acute cardiovascular syndrome with high mortalit...

Post-stroke hand gesture recognition via one-shot transfer learning using prototypical networks.

BACKGROUND: In-home rehabilitation systems are a promising, potential alternative to conventional th...

A deep learning-based automated diagnosis system for SPECT myocardial perfusion imaging.

Images obtained from single-photon emission computed tomography for myocardial perfusion imaging (MP...