Latest AI and machine learning research in congestive heart failure for healthcare professionals.
The pulse arrival time (PAT), the difference between the R-peak time of electrocardiogram (ECG) sign...
Deep learning (DL) has been applied for automatic left ventricle (LV) ejection fraction (EF) measure...
The endoprosthetic care of hip and knee joints introduces multiple materials into the human body. Me...
Zebrafish is a powerful and widely-used model system for a host of biological investigations, includ...
OBJECTIVE: To validate an artificial intelligence-augmented electrocardiogram (AI-ECG) algorithm for...
Virtual population generation is an emerging field in data science with numerous applications in hea...
Pneumothorax is a common pulmonary disease that can lead to dyspnea and can be life-threatening. X-r...
INTRODUCTION: Rate pressure product (the product of heart rate and systolic blood pressure) is a mea...
OBJECTIVE: At present, there is no consensus on the best strategy for interpreting the cardiopulmona...
There is not enough information about tinnitus and related parameters in patients with heart failure...
Clinical decision-making regarding treatments based on personal characteristics leads to effective h...
OBJECTIVES: The authors explored a deep neural network (DeepNN) model that integrates multidimension...
Few studies have addressed radiomics based differentiation of Glioblastoma (GBM) and intracranial me...
Premature all-cause mortality is high in patients receiving peritoneal dialysis (PD). The accurate a...
Transthyretin amyloid cardiomyopathy, an often unrecognized cause of heart failure, is now treatable...
Hypertrophic Cardiomyopathy (HCM) is the most common genetic heart disease in the US and is known to...
PURPOSE: To assess the potential of machine learning to predict low and high treatment demand in rea...
Conjunctival provocation test (CPT) is used to demonstrate clinical relevance to a specific allerge...
BACKGROUND: Genetic testing can determine family screening strategies and has prognostic and diagnos...
Machine learning approaches are increasingly suggested as tools to improve prediction of clinical ou...
BACKGROUND: Accurate identification of end-diastolic and end-systolic frames in echocardiographic ci...