Congress:
ECR24
Poster Number:
C-17087
Type:
EPOS Radiologist (scientific)
DOI:
10.26044/ecr2024/C-17087
Authorblock:
F. Souschek, P. Mildenberger, L. Müller, T. Jorg, M. C. Halfmann; Mainz/DE
Disclosures:
Fabio Souschek:
Nothing to disclose
Peter Mildenberger:
Nothing to disclose
Lukas Müller:
Nothing to disclose
Tobias Jorg:
Nothing to disclose
Moritz Christian Halfmann:
Nothing to disclose
Keywords:
Artificial Intelligence, Thorax, Plain radiographic studies, Comparative studies, Quality assurance
While diagnostic accuracy remained moderate to high for detecting opacities, consolidation, and pleural effusion in supine chest X-rays of ICU patients, the performance in detecting pneumothorax and cardiomegaly falls short of clinical applicability. Additionally, supine chest X-rays showed markedly lower positive and negative predictive values with a broader range, even though the prevalence of target findings was considerably higher in ICU patients. This highlights the importance of rigorous evaluation of AI tools prior to their application in new clinical settings.