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. 2025 Oct 13;12:1655302. doi: 10.3389/fmed.2025.1655302

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Copyright © 2025 Su, Chen, Wang, Song, Xu, Lin and Lin.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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Side-by-side calibration curves display predicted versus observed probabilities. Panel A (Train) shows three lines: clinical (blue), image (orange), and combined (green). Panel B (Test) also shows clinical, image, and combined lines. Each line is compared against the diagonal line representing perfect calibration. Both panels highlight discrepancies between predicted and observed values across different data sets. — Calibration curves for predicting treatment outcome. Calibration curves for the clinical model, image model, and combined model in the training (A) and test (B) cohorts. Calibration curves plot observed probability versus predicted probability, with a perfectly calibrated model following the diagonal line.