Congestive Heart Failure

A systematic review and meta-analysis on the performance of convolutional neural networks ECGs in the diagnosis of hypertrophic cardiomyopathy.

INTRODUCTION: Hypertrophic cardiomyopathy (HCM) is a leading cause of sudden cardiac death in younger individuals. Accurate diagnosis is crucial for management and improving patient outcomes. The application of convolutional Neural Networks (CNN), a type of AI modeling, to electrocardiogram (ECG) analysis, presents a promising and optimistic avenue for the detection of HCM. We conducted a meta-ana...

Enhancing cardiovascular disease classification in ECG spectrograms by using multi-branch CNN.

Cardiovascular disease (CVD) is caused by the abnormal functioning of the heart which results in a high mortality rate across the globe. The accurate and early prediction of various CVDs from the electrocardiogram (ECG) is vital for the prevention of deaths caused by CVD. Artificial intelligence (AI) is used to categorize and accurately predict various CVDs. Among different AI-based techniques, de...

Pregnancy-Induced Cardiomyopathy: What Case Managers Need to Know.

A new form of stethoscope with artificial intelligence (AI) capabilities may make the difference between early detection of pregnancy-induced cardiomy...

Deep Learning-Enabled Assessment of Right Ventricular Function Improves Prognostication After Transcatheter Edge-to-Edge Repair for Mitral Regurgitation.

BACKGROUND: Right ventricular (RV) function has a well-established prognostic role in patients with severe mitral regurgitation (MR) undergoing transc...

Development of a clinical-radiological nomogram for predicting severe postoperative peritumoral brain edema following intracranial meningioma resection.

OBJECTIVE: The goal of this study was to develop a nomogram that integrates clinical data to predict the likelihood of severe postoperative peritumora...

Predictive value of CT-based and AI-reconstructed 3D-TAPSE in patients undergoing transcatheter tricuspid valve repair.

BACKGROUND: The tricuspid annular plane systolic excursion (TAPSE) assessed by echocardiography has failed in predicting outcomes in patients with sev...

Predicting 28-day all-cause mortality in patients admitted to intensive care units with pre-existing chronic heart failure using the stress hyperglycemia ratio: a machine learning-driven retrospective cohort analysis.

Chronic heart failure (CHF) poses a significant threat to human health. The stress hyperglycemia ratio (SHR) is a novel metric for accurately assessin...

Predicting Blood Pressures for Pregnant Women by PPG and Personalized Deep Learning.

Blood pressure (BP) is predicted by this effort based on photoplethysmography (PPG) data to provide effective pre-warning of possible preeclampsia of ...

ECGEFNet: A two-branch deep learning model for calculating left ventricular ejection fraction using electrocardiogram.

Left ventricular systolic dysfunction (LVSD) and its severity are correlated with the prognosis of cardiovascular diseases. Early detection and monito...

Quantitative imaging for early detection and risk stratification of cardiovascular disease using 4D flow MRI and arterial spin labelling.

Heart failure (HF) significantly burdens global healthcare, necessitating early detection and precise risk stratification. Advanced imaging techniques...

Integration of Optical Coherence Tomography Images and Real-Life Clinical Data for Deep Learning Modeling: A Unified Approach in Prognostication of Diabetic Macular Edema.

The primary ocular effect of diabetes is diabetic retinopathy (DR), which is associated with diabetic microangiopathy. Diabetic macular edema (DME) ca...

Comparative investigation of lung adenocarcinoma and squamous cell carcinoma transcriptome to reveal potential candidate biomarkers: An explainable AI approach.

Patients with Non-Small Cell Lung Cancer (NSCLC) present a variety of clinical symptoms, such as dyspnea and chest pain, complicating accurate diagnos...

Development of a Self-Deploying Extra-Aortic Compression Device for Medium-Term Hemodynamic Stabilization: A Feasibility Study.

Hemodynamic stabilization is crucial in managing acute cardiac events, where compromised blood flow can lead to severe complications and increased mor...

Development of a Predictive Model of Occult Cancer After a Venous Thromboembolism Event Using Machine Learning: The CLOVER Study.

: Venous thromboembolism (VTE) can be the first manifestation of an underlying cancer. This study aimed to develop a predictive model to assess the ri...

Optimizing autonomous artificial intelligence diagnostics for neuro-ocular health in space missions.

Spaceflight-Associated Neuro-Ocular Syndrome (SANS) presents a critical risk in long-duration missions, with microgravity-induced changes that threate...

Machine learning for predicting acute myocardial infarction in patients with sepsis.

Acute myocardial infarction (AMI) and sepsis are the leading causes of high mortality rates in intensive care units. While sepsis frequently affects t...

Detection of late gadolinium enhancement in patients with hypertrophic cardiomyopathy using machine learning.

BACKGROUND: Late gadolinium enhancement (LGE) on cardiac magnetic resonance (CMR) in hypertrophic cardiomyopathy (HCM) typically represents myocardial...

Prediction of new-onset atrial fibrillation in patients with hypertrophic cardiomyopathy using machine learning.

AIMS: Atrial fibrillation (AF) is the most common sustained arrhythmia among patients with hypertrophic cardiomyopathy (HCM), leading to increased sym...

Artificial Intelligence Advancements in Cardiomyopathies: Implications for Diagnosis and Management of Arrhythmogenic Cardiomyopathy.

PURPOSE OF REVIEW: This review aims to explore the emerging potential of artificial intelligence (AI) in refining risk prediction, clinical diagnosis,...

Utilizing deep learning-based causal inference to explore vancomycin's impact on continuous kidney replacement therapy necessity in blood culture-positive intensive care unit patients.

Patients with positive blood cultures in the intensive care unit (ICU) are at high risk for septic acute kidney injury requiring continuous kidney rep...