Cardiovascular

Development of artificial intelligence-driven biosignal-sensitive cardiopulmonary resuscitation robot.

AIM OF THE STUDY: We evaluated whether an artificial intelligence (AI)-driven robot cardiopulmonary ...

Deep learning-based multimodal fusion of the surface ECG and clinical features in prediction of atrial fibrillation recurrence following catheter ablation.

BACKGROUND: Despite improvement in treatment strategies for atrial fibrillation (AF), a significant ...

Hierarchical Hybrid Networks for Automatic Pulmonary Blood Vessel Segmentation in Computed Tomography Images.

Pulmonary arterial hypertension (PAH) is considered the third most common cardiovascular disease aft...

A YOLOX-Based Deep Instance Segmentation Neural Network for Cardiac Anatomical Structures in Fetal Ultrasound Images.

Echocardiography is an essential procedure for the prenatal examination of the fetus for congenital ...

Commentary: Detection of Endoleak After Endovascular Aortic Repair Through Deep Learning Based on Non-contrast CT.

Artificial Intelligence and Health Inequities in Dietary Interventions on Atherosclerosis: A Narrative Review.

Poor diet is the top modifiable mortality risk factor globally, accounting for 11 million deaths ann...

Deep learning approaches for the detection of scar presence from cine cardiac magnetic resonance adding derived parametric images.

This work proposes a convolutional neural network (CNN) that utilizes different combinations of para...

Derivation and external validation of mass spectrometry-based proteomic model using machine learning algorithms to predict plaque rupture in patients with acute coronary syndrome.

BACKGROUND: A poor prognosis is associated with atherosclerotic plaque rupture (PR) despite after co...

Sex and population differences in the cardiometabolic continuum: a machine learning study using the UK Biobank and ELSA-Brasil cohorts.

BACKGROUND: The temporal relationships across cardiometabolic diseases (CMDs) were recently conceptu...

Non-Contact Blood Pressure Estimation From Radar Signals by a Stacked Deformable Convolution Network.

This study introduces a contactless blood pressure monitoring approach that combines conventional ra...

Modeling 3D Cardiac Contraction and Relaxation With Point Cloud Deformation Networks.

Global single-valued biomarkers, such as ejection fraction, are widely used in clinical practice to ...

Artificial intelligence in heart valve disease: diagnosis, innovation and treatment. A state-of-the-art review.

In recent years, artificial intelligence (AI) has been used to improve the precision of valvular hea...

Identifying Factors Associated With Fast Visual Field Progression in Patients With Ocular Hypertension Based on Unsupervised Machine Learning.

PRCIS: We developed unsupervised machine learning models to identify different subtypes of patients ...

A two-stage ensemble learning based prediction and grading model for PD-1/PD-L1 inhibitor-related cardiac adverse events: A multicenter retrospective study.

BACKGROUND: Immune-related cardiac adverse events (ircAEs) caused by programmed cell death protein-1...

Predictive ability of hypotension prediction index and machine learning methods in intraoperative hypotension: a systematic review and meta-analysis.

INTRODUCTION: Intraoperative Hypotension (IOH) poses a substantial risk during surgical procedures. ...

Improving cardiovascular risk prediction with machine learning: a focus on perivascular adipose tissue characteristics.

BACKGROUND: Timely prevention of major adverse cardiovascular events (MACEs) is imperative for reduc...

Rationale and design of the artificial intelligence scalable solution for acute myocardial infarction (ASSIST) study.

BACKGROUND: Acute coronary syndrome (ACS), specifically ST-segment elevation myocardial infarction i...

Automatic pipeline for segmentation of LV myocardium on quantitative MR T1 maps using deep learning model and computation of radial T1 and ECV values.

Native T1 mapping is a non-invasive technique used for early detection of diffused myocardial abnorm...

Combining robotics and functional electrical stimulation for assist-as-needed support of leg movements in stroke patients: A feasibility study.

PURPOSE: Rehabilitation technology can be used to provide intensive training in the early phases aft...

Gated SPECT-Derived Myocardial Strain Estimated From Deep-Learning Image Translation Validated From N-13 Ammonia PET.

RATIONALE AND OBJECTIVES: This study investigated the use of deep learning-generated virtual positro...

Machine learning enhances assessment of proficiency in endovascular aortic repair simulations.