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[R] Seeing arxiv endorser (eess.IV or cs.CV) CT lung nodule AI validation preprint

Reddit r/MachineLearning / 3/22/2026

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Key Points

  • The preprint analyzes a MONAI RetinaNet lung nodule detector using physics-guided acquisition parameter perturbation on the LIDC-IDRI dataset with LUNA16 weights.
  • It reports that increasing CT slice thickness to 5 mm yields a 42% relative drop in detection sensitivity compared with baseline, highlighting strong parameter sensitivity.
  • It also finds that dose reductions of 25–50% cause only about a 4 percentage-point loss in sensitivity, suggesting potential protocol trade-offs for efficiency.
  • The authors are seeking an endorsement from experts in eess.IV or cs.CV, indicating community validation for the arXiv submission.

Sorry, I know these requests can be annoying, but I’m a medical physicist and no one I know uses arXiv.

The preprint: post-deployment sensitivity analysis of a MONAI RetinaNet lung nodule detector using physics-guided acquisition parameter perturbation (LIDC-IDRI dataset, LUNA16 weights).

Key finding: 5mm slice thickness causes a 42% relative sensitivity drop vs baseline; dose reduction at 25-50% produces only ~4pp loss. Threshold sensitivity analysis confirms the result holds across confidence thresholds from 0.1–0.9.

Looking for an endorser in eess.IV or cs.CV. Takes 30 seconds. Happy to share the paper.

Thanks.

submitted by /u/californiaburritoman
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