Cardiovascular

Performance and clinical utility of an artificial intelligence-enabled tool for pulmonary embolism detection.

PURPOSE: Diagnosing pulmonary embolism (PE) is still challenging due to other conditions that can mi...

Deeper insights from deep learning: Enhanced myocardial perfusion assessments using multimodal artificial intelligence.

A Machine Learning Model for Predicting In-Hospital Mortality in Chinese Patients With ST-Segment Elevation Myocardial Infarction: Findings From the China Myocardial Infarction Registry.

BACKGROUND: Machine learning (ML) risk prediction models, although much more accurate than tradition...

Machine Learning Predicts Peripherally Inserted Central Catheters-Related Deep Vein Thrombosis Using Patient Features and Catheterization Technology Features.

This study aims to use patient feature and catheterization technology feature variables to train the...

The effect of laparoscopic pneumoperitoneum on patient's respiratory variation of inferior vena cava and stroke volume index: A randomized controlled study.

BACKGROUND: The establishment of pneumoperitoneum has impacts on patient's cardiovascular function. ...

Deep learning-based automatic ASPECTS calculation can improve diagnosis efficiency in patients with acute ischemic stroke: a multicenter study.

OBJECTIVES: The Alberta Stroke Program Early CT Score (ASPECTS), a systematic method for assessing i...

Evaluating the effectiveness of a sliding window technique in machine learning models for mortality prediction in ICU cardiac arrest patients.

Extensive research has been devoted to predicting ICU mortality, to assist clinical teams managing c...

Machine learning-based prediction model of lower extremity deep vein thrombosis after stroke.

This study aimed to apply machine learning (ML) techniques to develop and validate a risk prediction...

Evaluation of the Factors Influencing Blood Transfusion during Minimally Invasive Direct Coronary Artery Bypass Surgery.

INTRODUCTION: The objective of this study was to analyze the blood transfusion factors of minimally ...

Development of Clinically Validated Artificial Intelligence Model for Detecting ST-segment Elevation Myocardial Infarction.

STUDY OBJECTIVE: Although the importance of primary percutaneous coronary intervention has been emph...

Multi-modality deep learning-based [Ga]Ga-DOTA-FAPI-04 PET polar map generation: potential value in detecting reactive fibrosis after myocardial infarction.

PURPOSE: Generating polar map (PM) from [Ga]Ga-DOTA-FAPI-04 PET images is challenging and inaccurate...

Development and Validation of an Explainable Machine Learning Model for Predicting Myocardial Injury After Noncardiac Surgery in Two Centers in China: Retrospective Study.

BACKGROUND: Myocardial injury after noncardiac surgery (MINS) is an easily overlooked complication b...

Deep learning for intracranial aneurysm segmentation using CT angiography.

This study aimed to employ a two-stage deep learning method to accurately detect small aneurysms (4-...

Pitfalls in Developing Machine Learning Models for Predicting Cardiovascular Diseases: Challenge and Solutions.

In recent years, there has been explosive development in artificial intelligence (AI), which has bee...

MEFFNet: Forecasting Myoelectric Indices of Muscle Fatigue in Healthy and Post-Stroke During Voluntary and FES-Induced Dynamic Contractions.

Myoelectric indices forecasting is important for muscle fatigue monitoring in wearable technologies,...

Reduced response to regadenoson with increased weight: An artificial intelligence-based quantitative myocardial perfusion study.

BACKGROUND: There is conflicting evidence regarding the response to a fixed dose of regadenoson in p...

Transforming Echocardiography: The Role of Artificial Intelligence in Enhancing Diagnostic Accuracy and Accessibility.

Artificial intelligence (AI) has shown transformative potential in various medical fields, including...

Unlocking Tomorrow's Health Care: Expanding the Clinical Scope of Wearables by Applying Artificial Intelligence.

As an integral aspect of health care, digital technology has enabled modelling of complex relationsh...

An artificial intelligence-enabled electrocardiogram algorithm for the prediction of left atrial low-voltage areas in persistent atrial fibrillation.

OBJECTIVES: We aimed to construct an artificial intelligence-enabled electrocardiogram (ECG) algorit...

Artificial intelligence meets pulmonary hypertension: early detection for a late-presenting disease.

A Deep-Learning-Based CPR Action Standardization Method.

In emergency situations, ensuring standardized cardiopulmonary resuscitation (CPR) actions is crucia...