Eur Heart J Imaging Methods Pract
September 2023
Aims: Impaired standardization of echocardiograms may increase inter-operator variability. This study aimed to determine whether the real-time guidance of experienced sonographers by deep learning (DL) could improve the standardization of apical recordings.
Methods And Results: Patients ( = 88) in sinus rhythm referred for echocardiography were included.
Aims: Apical foreshortening leads to an underestimation of left ventricular (LV) volumes and an overestimation of LV ejection fraction and global longitudinal strain. Real-time guiding using deep learning (DL) during echocardiography to reduce foreshortening could improve standardization and reduce variability. We aimed to study the effect of real-time DL guiding during echocardiography on measures of LV foreshortening and inter-observer variability.
View Article and Find Full Text PDFProg Community Health Partnersh
July 2024
Background: Aquí Entre Nos (Between Us) is a community-based participatory research project to engage rural, ethno-racially diverse hotel housekeepers in a right to work state during a time of national anti-immigrant policy, wildfires and emergence of a global pandemic.
Objectives: We aimed to (1) build trust and social support with the hotel housekeeping community, (2) learn about the occupational health, safety, and workers' rights challenges, strategies, and solutions held by workers, and (3) develop a workforce-driven research and action agenda to improve labor and health conditions.
Methods: Participatory mixed methods rooted in popular education are described to form an advisory board and engage the workforce.