Heart failure (HF) affects millions of individuals and causes hundreds of thousands of deaths each year in the United States. Despite the public health burden, medical and device therapies for HF significantly improve clinical outcomes and, in a subs...
Journal of insurance medicine (New York, N.Y.)
39266001
Applications of Artificial Intelligence (AI) deep-learning models to screening for clinical conditions continue to evolve. Instances provided in this treatise include using a simple one-view PA chest radiograph to screen for Type 2 Diabetes Mellitus ...
Computer methods and programs in biomedicine
39236563
BACKGROUND: Acute heart failure (AHF) in the intensive care unit (ICU) is characterized by its criticality, rapid progression, complex and changeable condition, and its pathophysiological process involves the interaction of multiple organs and system...
Studies in health technology and informatics
39176932
Heart failure poses a significant global health burden with high prevalence and mortality rates. A promising possibility in this context is the constant monitoring of the patients through telemedicine. The aim of this work is to present a digital twi...
BACKGROUND: The improvement of controllers of left ventricular assist device (LVAD) technology supporting heart failure (HF) patients has enormous impact, given the high prevalence and mortality of HF in the population. The use of reinforcement learn...
For World Heart Day on September 24, 2024, the World Heart Federation urges nations to endorse national strategies for enhancing cardiovascular health. While advancements show promise in reducing atherosclerosis, addressing healthcare inequalities an...
BACKGROUND: Prior studies characterizing worsening heart failure events (WHFE) have been limited in using structured healthcare data from hospitalizations, and with little exploration of sociodemographic variation. The current study examined the impa...
AIMS: This study aims to develop and validate an optimal model for predicting worsening heart failure (WHF). Multiple machine learning (ML) algorithms were compared, and the results were interpreted using SHapley Additive exPlanations (SHAP). A clini...
AIMS: Abnormalities in specific echocardiographic parameters and cardiac biomarkers have been reported among individuals with diabetes. However, a comprehensive characterization of diabetic cardiomyopathy (DbCM), a subclinical stage of myocardial abn...
ASAIO journal (American Society for Artificial Internal Organs : 1992)
39231213
Accurate activity classification is essential for the advancement of closed-loop control for left ventricular assist devices (LVADs), as it provides necessary feedback to adapt device operation to the patient's current state. Therefore, this study ai...