Development and testing of a deep learning algorithm to detect lung consolidation among children with pneumonia using hand-held ultrasound.

ABSTRACT:

Background and objectives

Severe pneumonia is the leading cause of death among young children worldwide, disproportionately impacting children who lack access to advanced diagnostic imaging. Here our objectives were to develop and test the accuracy of an artificial intelligence algorithm for detecting features of pulmonary consolidation on point-of-care lung ultrasounds among hospitalized children.

Methods

This was a prospective, multicenter center study conducted at academic Emergency Department and Pediatric inpatient or intensive care units between 2018-2020. Pediatric participants from 18 months to 17 years old with suspicion of lower respiratory tract infection were enrolled. Bedside lung ultrasounds were performed using a Philips handheld Lumify C5-2 transducer and sta

SUBMITTER: Kessler D 

PROVIDER: S-EPMC11349203 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature