PDD-RRG: Posterior Diagnostic Decision for Study-level Radiology Report Generation
Proceedings of the Thirty-Fifth International Joint Conference on Artificial Intelligence. Main Track. Pages 2055-2063.
https://doi.org/10.24963/ijcai.2026/229
Keywords
- Multidisciplinary Topics and Applications: Health and medicine
- Computer Vision: Biomedical image analysis
- Multidisciplinary Topics and Applications: Bioinformatics
Abstract
Automatic radiology report generation (RRG) aims to simulate the workflow of radiologists, assisting them in clinical diagnosis. However, existing methods often fall short in utilizing all information relevant to the examination, as is typically done in clinical practice. Although some works attempt to incorporate multi-view images and historical data, these additional inputs may sometimes lead to avoidable diagnostic errors on the contrary. To address these challenges, we introduce a decision-making stage after report generation for the first time and propose a Posterior Diagnostic Decision framework (PDD-RRG) to integrate potentially conflicting diagnoses. Specifically, we create various subsets of input data and utilize an existing RRG model to generate reports from different perspectives. Then the Bayesian posterior probability and the learned thresholds for each clinical observation are calculated to obtain an aggregated diagnostic conclusion, which is subsequently used to refine the generated report. Experiments on MIMIC-CXR demonstrate that our proposed PDD-RRG can effectively enhance the clinical efficacy of existing RRG models without any retraining.
@inproceedings{ijcai2026p229,
title = {PDD-RRG: Posterior Diagnostic Decision for Study-level Radiology Report Generation},
author = {Yu, Yang and Ji, Yiming and Dai, Bin and Zhang, Dong and Zhou, Zhiyong and Li, Shoushan and Dai, Yakang},
booktitle = {Proceedings of the Thirty-Fifth International Joint Conference on
Artificial Intelligence, {IJCAI-26}},
publisher = {International Joint Conferences on Artificial Intelligence Organization},
editor = {Diego Calvanese},
pages = {2055--2063},
year = {2026},
month = {8},
note = {Main Track},
doi = {10.24963/ijcai.2026/229},
url = {https://doi.org/10.24963/ijcai.2026/229},
}
TY - CPAPER TI - PDD-RRG: Posterior Diagnostic Decision for Study-level Radiology Report Generation AU - Yu, Yang AU - Ji, Yiming AU - Dai, Bin AU - Zhang, Dong AU - Zhou, Zhiyong AU - Li, Shoushan AU - Dai, Yakang T2 - Proceedings of the Thirty-Fifth International Joint Conference on Artificial Intelligence, IJCAI-26 PB - International Joint Conferences on Artificial Intelligence Organization PY - 2026 SP - 2055 EP - 2063 DO - 10.24963/ijcai.2026/229 UR - https://doi.org/10.24963/ijcai.2026/229 ER -Copied
Machine-readable versions of this paper, for tools and AI agents: