Health AI Central
Peer-Reviewed Publication
AJR Am J Roentgenol2026October 14, 2026Journal Article

Radiomic Features Extracted From Manual and Deep Learning-Based Segmentations: Comparison of Agreement, Bias, and Model Performance.

Jonathan A Dudley1,2, Zach Taylor1,2, Hailong Li1,2,3, Lisa Qiu2, Jonathan R Dillman2,4,3, Andrew T Trout2,4,3
1Imaging Research Center, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA.
2Department of Radiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA.
3Department of Radiology, University of Cincinnati College of Medicine, Cincinnati, OH, USA.
4Department of Pediatrics, College of Medicine, University of Cincinnati, Cincinnati, OH, USA.
PubMed DOI

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.