{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,4]],"date-time":"2026-05-04T08:06:33Z","timestamp":1777881993483,"version":"3.51.4"},"reference-count":59,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T00:00:00Z","timestamp":1772323200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T00:00:00Z","timestamp":1772323200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T00:00:00Z","timestamp":1772323200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T00:00:00Z","timestamp":1772323200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T00:00:00Z","timestamp":1772323200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T00:00:00Z","timestamp":1772323200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T00:00:00Z","timestamp":1772323200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100014188","name":"Ministry of Science and ICT, South Korea","doi-asserted-by":"publisher","award":["RS-2024-00401899"],"award-info":[{"award-number":["RS-2024-00401899"]}],"id":[{"id":"10.13039\/501100014188","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100014188","name":"Ministry of Science and ICT, South Korea","doi-asserted-by":"publisher","award":["RS-2025-24683103"],"award-info":[{"award-number":["RS-2025-24683103"]}],"id":[{"id":"10.13039\/501100014188","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100010418","name":"Institute of Information &amp; Communications Technology Planning &amp; Evaluation","doi-asserted-by":"publisher","award":["IITP-2025-RS-2024-00360227"],"award-info":[{"award-number":["IITP-2025-RS-2024-00360227"]}],"id":[{"id":"10.13039\/501100010418","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003725","name":"National Research Foundation of Korea","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100003725","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003716","name":"Korea Basic Science Institute","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100003716","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Expert Systems with Applications"],"published-print":{"date-parts":[[2026,3]]},"DOI":"10.1016\/j.eswa.2025.130633","type":"journal-article","created":{"date-parts":[[2025,12,4]],"date-time":"2025-12-04T16:32:47Z","timestamp":1764865967000},"page":"130633","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":1,"special_numbering":"C","title":["CLARIFID: Improving radiology report generation by reinforcing clinically accurate impressions and enforcing detailed findings"],"prefix":"10.1016","volume":"303","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-6318-1244","authenticated-orcid":false,"given":"Kyeongkyu","family":"Lee","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-4330-5128","authenticated-orcid":false,"given":"Seonghwan","family":"Yoon","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2764-3730","authenticated-orcid":false,"given":"Hongki","family":"Lim","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"78","reference":[{"key":"10.1016\/j.eswa.2025.130633_bib0001","unstructured":"Brown, B., Juravsky, J., Ehrlich, R., Clark, R., Le, Q. V., R\u2019e, C., & Mirhoseini, A. (2024). Large language monkeys: Scaling inference compute with repeated sampling. arXiv: 2407.21787."},{"key":"10.1016\/j.eswa.2025.130633_bib0002","series-title":"2024 IEEE\/CVF conference on computer vision and pattern recognition (CVPR)","first-page":"14194","article-title":"Instance-level expert knowledge and aggregate discriminative attention for radiology report generation","author":"Bu","year":"2024"},{"key":"10.1016\/j.eswa.2025.130633_bib0003","series-title":"Neural information processing systems","article-title":"Are more LLM calls all you need? Towards the scaling properties of compound AI systems","author":"Chen","year":"2024"},{"key":"10.1016\/j.eswa.2025.130633_bib0004","series-title":"Annual meeting of the association for computational linguistics","article-title":"Cross-modal memory networks for radiology report generation","author":"Chen","year":"2022"},{"key":"10.1016\/j.eswa.2025.130633_bib0005","series-title":"Proceedings of the 2020 conference on empirical methods in natural language processing","article-title":"Generating radiology reports via memory-driven transformer","author":"Chen","year":"2020"},{"key":"10.1016\/j.eswa.2025.130633_bib0006","unstructured":"Cobbe, K., Kosaraju, V., Bavarian, M., Chen, M., Jun, H., Kaiser, L., Plappert, M., Tworek, J., Hilton, J., Nakano, R., Hesse, C., & Schulman, J. (2021). Training verifiers to solve math word problems. ArXiv, abs\/2110.14168."},{"key":"10.1016\/j.eswa.2025.130633_bib0007","unstructured":"DeepSeek-AI, Guo, D., Yang, D., Zhang, H., Song, J.-M., Zhang, R., Xu, R., Zhu, Q., Ma, S., Wang, P., Bi, X., Zhang, X., Yu, X., Wu, Y., Wu, Z. F., Gou, Z., Shao, Z., Li, Z., Gao, Z., & Zhang, Z. (2025). DeepSeek-R1: Incentivizing reasoning capability in LLMs via reinforcement learning. arXiv: 2501.12948."},{"key":"10.1016\/j.eswa.2025.130633_bib0008","series-title":"Conference on empirical methods in natural language processing","article-title":"Improving the factual correctness of radiology report generation with semantic rewards","author":"Delbrouck","year":"2022"},{"issue":"2","key":"10.1016\/j.eswa.2025.130633_bib0009","doi-asserted-by":"crossref","first-page":"304","DOI":"10.1093\/jamia\/ocv080","article-title":"Preparing a collection of radiology examinations for distribution and retrieval","volume":"23","author":"Demner-Fushman","year":"2015","journal-title":"Journal of the American Medical Informatics Association : JAMIA"},{"key":"10.1016\/j.eswa.2025.130633_bib0010","unstructured":"Dhariwal, P., Hesse, C., Klimov, O., Nichol, A., Plappert, M., Radford, A., Schulman, J., Sidor, S., Wu, Y., & Zhokhov, P. (2017). OpenAI baselines. GitHub repository. https:\/\/github.com\/openai\/baselines."},{"key":"10.1016\/j.eswa.2025.130633_bib0011","series-title":"Findings of the association for computational linguistics: EMNLP 2024","article-title":"LLM self-correction with DeCRIM: Decompose, critique, and refine for enhanced following of instructions with multiple constraints","author":"Ferraz","year":"2024"},{"issue":"04","key":"10.1016\/j.eswa.2025.130633_bib0012","doi-asserted-by":"crossref","first-page":"475","DOI":"10.4338\/ACI-2012-06-RA-0022","article-title":"Insight into the sharing of medical images: Physician, other health care providers, and staff experience in a variety of medical settings","volume":"03","author":"Ge","year":"2012","journal-title":"Applied Clinical Informatics"},{"key":"10.1016\/j.eswa.2025.130633_bib0013","series-title":"2024 IEEE\/CVF winter conference on applications of computer vision (WACV)","first-page":"7980","article-title":"Complex organ mask guided radiology report generation","author":"Gu","year":"2023"},{"key":"10.1016\/j.eswa.2025.130633_bib0014","series-title":"Proceedings of the 61st annual meeting of the association for computational linguistics (volume 1: Long papers)","first-page":"8108","article-title":"ORGAN: Observation-guided radiology report generation via tree reasoning","author":"Hou","year":"2023"},{"key":"10.1016\/j.eswa.2025.130633_bib0015","series-title":"First conference on language modeling","article-title":"The n+ implementation details of RLHF with PPO: A case study on TL;DR summarization","author":"Huang","year":"2024"},{"key":"10.1016\/j.eswa.2025.130633_bib0016","series-title":"2023 IEEE\/CVF conference on computer vision and pattern recognition (CVPR)","first-page":"19809","article-title":"KiUT: Knowledge-injected u-transformer for radiology report generation","author":"Huang","year":"2023"},{"key":"10.1016\/j.eswa.2025.130633_bib0017","unstructured":"Irvine, R. P., Boubert, D., Raina, V., Liusie, A., Zhu, Z., Mudupalli, V., Korshuk, A., Liu, Z. J., Cremer, F., Assassi, V., Beauchamp, C.-C., Lu, X., Rialan, T., & Beauchamp, W. (2023). Rewarding chatbots for real-world engagement with millions of users. arXiv: 2303.06135."},{"key":"10.1016\/j.eswa.2025.130633_bib0018","series-title":"Proceedings of the neural information processing systems track on datasets and benchmarks","article-title":"RadGraph:Extracting clinical entities and relations from radiology reports","volume":"vol. 1","author":"Jain","year":"2021"},{"key":"10.1016\/j.eswa.2025.130633_bib0019","series-title":"Proceedings of the thirty-eighth AAAI conference on artificial intelligence and thirty-sixth conference on innovative applications of artificial intelligence and fourteenth symposium on educational advances in artificial intelligence","article-title":"PromptMRG: Diagnosis-driven prompts for medical report generation","author":"Jin","year":"2024"},{"key":"10.1016\/j.eswa.2025.130633_bib0020","series-title":"Findings of the association for computational linguistics: ACL 2025","first-page":"9989","article-title":"\u201cWell, keep thinking\u201d: Enhancing LLM reasoning with adaptive injection decoding","author":"Jin","year":"2025"},{"key":"10.1016\/j.eswa.2025.130633_bib0021","unstructured":"Johnson, A. E. W., Pollard, T. J., Greenbaum, N. R., Lungren, M. P., Deng, C.-y., Peng, Y., Lu, Z., Mark, R. G., Berkowitz, S. J., & Horng, S. (2019). MIMIC-CXR-JPG, a large publicly available database of labeled chest radiographs. https:\/\/arxiv.org\/abs\/1901.07042."},{"key":"10.1016\/j.eswa.2025.130633_bib0022","series-title":"International conference on machine learning","article-title":"Rlaif vs. RLHF: Scaling reinforcement learning from human feedback with ai feedback","author":"Lee","year":"2023"},{"key":"10.1016\/j.eswa.2025.130633_bib0023","series-title":"2023 IEEE\/CVF conference on computer vision and pattern recognition (CVPR)","first-page":"3334","article-title":"Dynamic graph enhanced contrastive learning for chest x-ray report generation","author":"Li","year":"2023"},{"key":"10.1016\/j.eswa.2025.130633_bib0024","series-title":"European conference on computer vision","article-title":"Contrastive learning with counterfactual explanations for radiology report generation","author":"Li","year":"2024"},{"key":"10.1016\/j.eswa.2025.130633_bib0025","doi-asserted-by":"crossref","first-page":"1092","DOI":"10.1126\/science.abq1158","article-title":"Competition-level code generation with alphacode","volume":"378","author":"Li","year":"2022","journal-title":"Science"},{"key":"10.1016\/j.eswa.2025.130633_bib0026","series-title":"European conference on computer vision","article-title":"Microsoft COCO: Common objects in context","author":"Lin","year":"2014"},{"key":"10.1016\/j.eswa.2025.130633_bib0027","series-title":"AAAI conference on artificial intelligence","doi-asserted-by":"crossref","DOI":"10.5772\/intechopen.111293","article-title":"Bootstrapping large language models for radiology report generation","author":"Liu","year":"2024"},{"key":"10.1016\/j.eswa.2025.130633_bib0028","doi-asserted-by":"crossref","first-page":"13748","DOI":"10.1109\/CVPR46437.2021.01354","article-title":"Exploring and distilling posterior and prior knowledge for radiology report generation","author":"Liu","year":"2021","journal-title":"2021 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)"},{"key":"10.1016\/j.eswa.2025.130633_bib0029","series-title":"2025 IEEE\/CVF conference on computer vision and pattern recognition (CVPR)","first-page":"10348","article-title":"Enhanced contrastive learning with multi-view longitudinal data for chest X-ray report generation","author":"Liu","year":"2025"},{"key":"10.1016\/j.eswa.2025.130633_bib0030","series-title":"International conference on medical image computing and computer-assisted intervention","article-title":"MRScore: Evaluating medical report with LLM-based reward system","author":"Liu","year":"2024"},{"key":"10.1016\/j.eswa.2025.130633_bib0031","series-title":"2022 IEEE\/CVF conference on computer vision and pattern recognition (CVPR)","first-page":"11999","article-title":"Swin transformer V2: Scaling up capacity and resolution","author":"Liu","year":"2021"},{"key":"10.1016\/j.eswa.2025.130633_bib0032","series-title":"International conference on learning representations","article-title":"Decoupled weight decay regularization","author":"Loshchilov","year":"2017"},{"key":"10.1016\/j.eswa.2025.130633_bib0033","series-title":"Advances in neural information processing systems","first-page":"46534","article-title":"Self-refine: Iterative refinement with self-feedback","volume":"vol. 36","author":"Madaan","year":"2023"},{"key":"10.1016\/j.eswa.2025.130633_bib0034","doi-asserted-by":"crossref","DOI":"10.18653\/v1\/2022.clinicalnlp-1.5","article-title":"RRED : A radiology report error detector based on deep learning framework","author":"Min","year":"2022","journal-title":"Proceedings of the 4th Clinical Natural Language Processing Workshop"},{"key":"10.1016\/j.eswa.2025.130633_bib0035","series-title":"Proceedings of the 2021 conference of the North American chapter of the association for computational linguistics: Human language technologies","first-page":"5288","article-title":"Improving factual completeness and consistency of image-to-text radiology report generation","author":"Miura","year":"2021"},{"key":"10.1016\/j.eswa.2025.130633_bib0036","doi-asserted-by":"crossref","unstructured":"Muennighoff, N., Yang, Z., Shi, W., Li, X. L., Li, F.-F., Hajishirzi, H., Zettlemoyer, L. S., Liang, P., Cand\u00e8s, E. J., & Hashimoto, T. (2025). S1: Simple test-time scaling. arXiv: 2501.19393.","DOI":"10.18653\/v1\/2025.emnlp-main.1025"},{"key":"10.1016\/j.eswa.2025.130633_bib0037","doi-asserted-by":"crossref","unstructured":"Ouyang, L., Wu, J., Jiang, X., Almeida, D., Wainwright, C., Mishkin, P., Zhang, C., Agarwal, S., Slama, K., Ray, A., Schulman, J., Hilton, J., Kelton, F., Miller, L., Simens, M., Askell, A., Welinder, P., Christiano, P. F., Leike, J., & Lowe, R. (2022). Training language models to follow instructions with human feedback. In S. Koyejo, S. Mohamed, A. Agarwal, D. Belgrave, K. Cho, & A. Oh (Eds.), Advances in Neural Information Processing Systems (pp. 27730\u201327744). Curran Associates, Inc.(vol. 35).","DOI":"10.52202\/068431-2011"},{"key":"10.1016\/j.eswa.2025.130633_bib0038","series-title":"Findings","article-title":"Reinforced cross-modal alignment for radiology report generation","author":"Qin","year":"2022"},{"key":"10.1016\/j.eswa.2025.130633_bib0039","unstructured":"Radford, A., Wu, J., Child, R., Luan, D., Amodei, D., & Sutskever, I. (2019). Language models are unsupervised multitask learners."},{"key":"10.1016\/j.eswa.2025.130633_bib0040","series-title":"Thirty-seventh conference on neural information processing systems","article-title":"Direct preference optimization: Your language model is secretly a reward model","author":"Rafailov","year":"2023"},{"key":"10.1016\/j.eswa.2025.130633_bib0041","unstructured":"Schulman, J., Moritz, P., Levine, S., Jordan, M. I., & Abbeel, P. (2015). High-dimensional continuous control using generalized advantage estimation. arXiv: 1506.02438."},{"key":"10.1016\/j.eswa.2025.130633_bib0042","unstructured":"Schulman, J., Wolski, F., Dhariwal, P., Radford, A., & Klimov, O. (2017). Proximal policy optimization algorithms. arXiv: 1707.06347."},{"key":"10.1016\/j.eswa.2025.130633_bib0043","doi-asserted-by":"crossref","first-page":"336","DOI":"10.1007\/s11263-019-01228-7","article-title":"Grad-CAM: Visual explanations from deep networks via gradient-based localization","volume":"128","author":"Selvaraju","year":"2016","journal-title":"International Journal of Computer Vision"},{"key":"10.1016\/j.eswa.2025.130633_bib0044","unstructured":"Shen, H., Liu, P., Li, J., Fang, C., Ma, Y., Liao, J., Shen, Q., Zhang, Z., Zhao, K., Zhang, Q., Xu, R., & Zhao, T. (2025). VLM-R1: A stable and generalizable R1-style large vision-language model. arXiv: 2504.07615."},{"key":"10.1016\/j.eswa.2025.130633_bib0045","series-title":"Neural information processing systems","article-title":"Reflexion: Language agents with verbal reinforcement learning","author":"Shinn","year":"2023"},{"key":"10.1016\/j.eswa.2025.130633_bib0046","series-title":"Conference on empirical methods in natural language processing","article-title":"CheXbert: Combining automatic labelers and expert annotations for accurate radiology report labeling using BERT","author":"Smit","year":"2020"},{"key":"10.1016\/j.eswa.2025.130633_bib0047","series-title":"Proceedings of the 2025 conference of the nations of the Americas chapter of the association for computational linguistics: Human language technologies (volume 1: Long papers)","first-page":"4195","article-title":"The good, the bad, and the greedy: Evaluation of LLMs should not ignore non-determinism","author":"Song","year":"2025"},{"key":"10.1016\/j.eswa.2025.130633_bib0048","series-title":"2023 IEEE\/CVF conference on computer vision and pattern recognition (CVPR)","first-page":"7433","article-title":"Interactive and explainable region-guided radiology report generation","author":"Tanida","year":"2023"},{"key":"10.1016\/j.eswa.2025.130633_bib0049","first-page":"33536","article-title":"Multi-granularity cross-modal alignment for generalized medical visual representation learning","volume":"35","author":"Wang","year":"2022","journal-title":"Advances in Neural Information Processing Systems"},{"key":"10.1016\/j.eswa.2025.130633_bib0050","series-title":"The eleventh international conference on learning representations","article-title":"Self-consistency improves chain of thought reasoning in language models","author":"Wang","year":"2023"},{"key":"10.1016\/j.eswa.2025.130633_bib0051","series-title":"2023 IEEE\/CVF conference on computer vision and pattern recognition (CVPR)","first-page":"11558","article-title":"METransformer: Radiology report generation by transformer with multiple learnable expert tokens","author":"Wang","year":"2023"},{"key":"10.1016\/j.eswa.2025.130633_bib0052","article-title":"R2genGPT: Radiology report generation with frozen LLMs","volume":"abs\/2309.09812","author":"Wang","year":"2023","journal-title":"Meta-Radiology"},{"key":"10.1016\/j.eswa.2025.130633_bib0053","series-title":"AAAI\u201925\/IAAI\u201925\/EAAI\u201925","article-title":"LLM-RG4: Flexible and factual radiology report generation across diverse input contexts","author":"Wang","year":"2025"},{"key":"10.1016\/j.eswa.2025.130633_bib0054","unstructured":"Wei, J., Wang, X., Schuurmans, D., Bosma, M., Chi, E. H., Xia, F., Le, Q., & Zhou, D. (2022). Chain of thought prompting elicits reasoning in large language models. arXiv: 2201.11903."},{"key":"10.1016\/j.eswa.2025.130633_bib0055","series-title":"AAAI conference on artificial intelligence","article-title":"Radiology report generation via multi-objective preference optimization","author":"Xiao","year":"2024"},{"key":"10.1016\/j.eswa.2025.130633_bib0056","unstructured":"Xie, T., Gao, Z., Ren, Q., Luo, H., Hong, Y., Dai, B., Zhou, J., Qiu, K., Wu, Z., & Luo, C. (2025). Logic-RL: Unleashing LLM reasoning with rule-based reinforcement learning. arXiv: 2502.14768."},{"key":"10.1016\/j.eswa.2025.130633_bib0057","series-title":"First conference on language modeling","article-title":"Quiet-STar: Language models can teach themselves to think before speaking","author":"Zelikman","year":"2024"},{"key":"10.1016\/j.eswa.2025.130633_bib0058","doi-asserted-by":"crossref","first-page":"4470","DOI":"10.1109\/TMI.2024.3424505","article-title":"Attribute prototype-guided iterative scene graph for explainable radiology report generation","volume":"43","author":"Zhang","year":"2024","journal-title":"IEEE Transactions on Medical Imaging"},{"key":"10.1016\/j.eswa.2025.130633_bib0059","series-title":"AAAI conference on artificial intelligence","article-title":"When radiology report generation meets knowledge graph","author":"Zhang","year":"2020"}],"container-title":["Expert Systems with Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0957417425042484?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0957417425042484?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T00:59:20Z","timestamp":1777597160000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0957417425042484"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,3]]},"references-count":59,"alternative-id":["S0957417425042484"],"URL":"https:\/\/doi.org\/10.1016\/j.eswa.2025.130633","relation":{},"ISSN":["0957-4174"],"issn-type":[{"value":"0957-4174","type":"print"}],"subject":[],"published":{"date-parts":[[2026,3]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"CLARIFID: Improving radiology report generation by reinforcing clinically accurate impressions and enforcing detailed findings","name":"articletitle","label":"Article Title"},{"value":"Expert Systems with Applications","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.eswa.2025.130633","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2025 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"130633"}}