Commercial AI solutions in detecting COVID-19 pneumonia in chest CT: not yet ready for clinical implementation?
Florian JungmannLukas MüllerFelix HahnMaximilian WeustenfeldAnn-Kathrin DapperAline Mähringer-KunzDirk GraafenChristoph DüberDarius SchafighDaniel Pinto Dos SantosPeter MildenbergerRoman KloecknerPublished in: European radiology (2021)
• Commercial AI solutions achieved a sensitivity and specificity ranging from 62 to 96% and from 31 to 80%, respectively, in identifying patients suspicious for COVID-19 in a clinical dataset. • Sensitivity remained within the same range, while specificity was even lower in subgroup analysis of CT studies with ground-glass opacities, and interrater agreement between the commercial AI solutions was minimal to nonexistent. • Thus, commercial AI solutions have the potential to be integrated as alert tools for the detection of patients with lung changes suspicious for COVID-19 pneumonia in a clinical routine workflow, if further improvement is made.
Keyphrases
- coronavirus disease
- sars cov
- artificial intelligence
- ejection fraction
- machine learning
- contrast enhanced
- randomized controlled trial
- clinical trial
- magnetic resonance imaging
- magnetic resonance
- respiratory syndrome coronavirus
- quality improvement
- acute respiratory distress syndrome
- patient reported outcomes
- label free
- peritoneal dialysis
- human health
- real time pcr