AI Medical Compendium Journal:
Frontiers in cardiovascular medicine

Showing 21 to 30 of 38 articles

Algorithm for predicting valvular heart disease from heart sounds in an unselected cohort.

Frontiers in cardiovascular medicine
OBJECTIVE: This study aims to assess the ability of state-of-the-art machine learning algorithms to detect valvular heart disease (VHD) from digital heart sound recordings in a general population that includes asymptomatic cases and intermediate stag...

Improved stacking ensemble learning based on feature selection to accurately predict warfarin dose.

Frontiers in cardiovascular medicine
BACKGROUND: With the rapid development of artificial intelligence, prediction of warfarin dose via machine learning has received more and more attention. Since the dose prediction involve both linear and nonlinear problems, traditional machine learni...

Long-term results of ablation index guided atrial fibrillation ablation: insights after 5+ years of follow-up from the MPH AF Ablation Registry.

Frontiers in cardiovascular medicine
BACKGROUND: Catheter ablation (CA) for symptomatic atrial fibrillation (AF) offers the best outcomes for patients. Despite the benefits of CA, a significant proportion of patients suffer a recurrence; hence, there is scope to potentially improve outc...

Identification of hub genes in heart failure by integrated bioinformatics analysis and machine learning.

Frontiers in cardiovascular medicine
OBJECTIVE: To screen feature genes of heart failure patients through machine learning methods, in order to identify characteristic genes driving heart failure and investigate the progression of heart failure.

Navigating the AI frontiers in cardiovascular research: a bibliometric exploration and topic modeling.

Frontiers in cardiovascular medicine
Artificial intelligence (AI) has emerged as a promising field in cardiovascular disease (CVD) research, offering innovative approaches to enhance diagnosis, treatment, and patient outcomes. In this study, we conducted bibliometric analysis combined w...

Does artificial intelligence enhance physician interpretation of optical coherence tomography: insights from eye tracking.

Frontiers in cardiovascular medicine
BACKGROUND AND OBJECTIVES: The adoption of optical coherence tomography (OCT) in percutaneous coronary intervention (PCI) is limited by need for real-time image interpretation expertise. Artificial intelligence (AI)-assisted Ultreon™ 2.0 software cou...

Clinical service evaluation of the feasibility and reproducibility of novel artificial intelligence based-echocardiographic quantification of global longitudinal strain and left ventricular ejection fraction in trastuzumab-treated patients.

Frontiers in cardiovascular medicine
INTRODUCTION: Cardiotoxicity is a potential prognostically important complication of certain chemotherapeutic agents that may result in preclinical or overt clinical heart failure. In some cases, chemotherapy must be withheld when left ventricular (L...

Artificial intelligence-enabled 8-lead ECG detection of atrial septal defect among adults: a novel diagnostic tool.

Frontiers in cardiovascular medicine
BACKGROUND: Patients with atrial septal defect (ASD) exhibit distinctive electrocardiogram (ECG) patterns. However, ASD cannot be diagnosed solely based on these differences. Artificial intelligence (AI) has been widely used for specifically diagnosi...

Artificial Intelligence-A Good Assistant to Multi-Modality Imaging in Managing Acute Coronary Syndrome.

Frontiers in cardiovascular medicine
Acute coronary syndrome is the leading cause of cardiac death and has a significant impact on patient prognosis. Early identification and proper management are key to ensuring better outcomes and have improved significantly with the development of va...