ArticlePeerJ2026
Clinical study of
Article in PeerJ, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: This study aimed to assess the diagnostic value of Methods: A total of 222 patients with Solid pulmonary nodules were retrospectively analyzed and randomly divided into two groups: a training set ( Results: A total of eleven, nine, and fourteen optimal features were identified for the CT, PET, and PET+CT groups, respectively. In the validation set, the Area Under the Curve (AUC) values for the CT models ranged from 0.731 to 0.831, for the PET models from 0.746 to 0.810, and for the PET+CT models from 0.800 to 0.847. Among these, the PET+CT model developed using the Random Forest (RF) classifier demonstrated the best diagnostic performance, with an AUC of 0.847, sensitivity of 0.804, and specificity of 0.821. Decision curve analysis (DCA) confirmed that the model has favorable clinical utility, while calibration curves showed a good agreement between predicted and observed outcomes. Conclusion: The PET+CT radiomics models outperformed the single-modality models in distinguishing Solid pulmonary nodules adenocarcinoma from inflammatory lesions. Overall, the RF-based PET+CT model achieved the highest diagnostic efficacy and indicates promising potential for clinical application.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.