Health AI Central
Peer-Reviewed Publication
Pediatr Rep2026;18(5)September 11, 2026Journal Article

Review of Artificial Intelligence for Automated Assessment of Lines, Drains, and Airways on Pediatric and Adult Chest Radiographs.

Junqi Wang1,2, Lili He1,2,3,4,5, Gary R Schooler2,5, Alexander J Towbin2,3,5, Hailong Li1,2,3,5
1Imaging Research Center, Cincinnati Children's Hospital Medical Center, Cincinnati, OH 45229, USA.
2Department of Radiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH 45229, USA.
3Artificial Intelligence Imaging Research Center, Cincinnati Children's Hospital Medical Center, Cincinnati, OH 45229, USA.
4Computer Science, Biomedical Engineering, Biomedical Informatics, University of Cincinnati College of Medicine, Cincinnati, OH 45229, USA.
5Department of Radiology, University of Cincinnati College of Medicine, Cincinnati, OH 45229, USA.
PubMed PMC DOI PDF

Abstract

The accurate placement of lines, drains, and airways (LDAs) is essential for the safe management of critically ill patients, as malpositioned medical devices can result in severe complications ranging from ineffective treatment to life-threatening injury. Chest radiography (CXR) is the primary imaging modality for confirming the placement of many LDAs; however, the growing volume and complexity of…

Create a free account to keep reading

Free members get 10 full research views every month across publications, clinical trials, FDA clearances, adverse events, and NIH grants. No credit card required.

Create Free AccountSign In

Want unlimited research access? See Pro plans

Data Accuracy Notice: Research intelligence on Health AI Central is aggregated from public sources (PubMed, ClinicalTrials.gov, FDA, NIH, CMS, and others) and refreshed nightly. Classifications and derived metrics are produced by automated methods described in our Methodology. We recommend verifying critical data points against the primary sources before making decisions.