{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,14]],"date-time":"2026-07-14T07:04:19Z","timestamp":1784012659065,"version":"3.55.0"},"publisher-location":"Singapore","reference-count":26,"publisher":"Springer Nature Singapore","isbn-type":[{"value":"9789819234943","type":"print"},{"value":"9789819234950","type":"electronic"}],"license":[{"start":{"date-parts":[[2026,7,15]],"date-time":"2026-07-15T00:00:00Z","timestamp":1784073600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,7,15]],"date-time":"2026-07-15T00:00:00Z","timestamp":1784073600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2027]]},"DOI":"10.1007\/978-981-92-3495-0_19","type":"book-chapter","created":{"date-parts":[[2026,7,14]],"date-time":"2026-07-14T06:11:05Z","timestamp":1784009465000},"page":"221-232","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Prior-Driven Medical Report Generation via Graph-Momentum Diagnostic Modeling and Knowledge-Enhanced Prompt Initialization"],"prefix":"10.1007","author":[{"given":"Qianyao","family":"Peng","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shaoguo","family":"Cui","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Minjie","family":"Deng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Liang","family":"Xiong","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,7,15]]},"reference":[{"key":"19_CR1","unstructured":"Banerjee, A., Lavie, A.: METEOR: an automatic metric for MT evaluation with improved correlation with human judgments. In: Proceedings of the ACL Workshop on Intrinsic and Extrinsic Evaluation Measures for Machine Translation And\/Or Summarization, pp. 65\u201372 (2005)"},{"key":"19_CR2","doi-asserted-by":"crossref","unstructured":"Chen, Z., Song, Y., Chang, T.-H., Wan, X.: Generating radiology reports via memory-driven transformer. In: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), pp. 1439\u20131449. Conference Name: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) Place: Online Publisher: Association for Computational Linguistics (2020)","DOI":"10.18653\/v1\/2020.emnlp-main.112"},{"key":"19_CR3","doi-asserted-by":"crossref","unstructured":"Demner-Fushman, D., et al.: Preparing a collection of radiology examinations for distribution and retrieval. J. Am. Med. Inform. Assoc.: JAMIA 23, 2:304\u201310 (2015)","DOI":"10.1093\/jamia\/ocv080"},{"key":"19_CR4","unstructured":"Ge, C., et al.: Domain adaptation via prompt learning. IEEE Transactions on Neural Networks and Learning Systems (2023)"},{"key":"19_CR5","doi-asserted-by":"crossref","unstructured":"Huang, Z., Zhang, X., Zhang, S.: Kiut: knowledge-injected u-transformer for radiology report generation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 19809\u201319818 (2023)","DOI":"10.1109\/CVPR52729.2023.01897"},{"key":"19_CR6","doi-asserted-by":"crossref","unstructured":"Jin, H., Che, H., Lin, Y., Chen, H.: Promptmrg: diagnosis-driven prompts for medical report generation. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 38, Issue 3, pp. 2607\u20132615 (2024)","DOI":"10.1609\/aaai.v38i3.28038"},{"key":"19_CR7","doi-asserted-by":"crossref","unstructured":"Jing, B., Xie, P., Xing, E.: On the automatic generation of medical imaging reports. In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics, volume 1: long papers, pp. 2577\u20132586 (2018)","DOI":"10.18653\/v1\/P18-1240"},{"key":"19_CR8","unstructured":"Johnson, A.E.W., et al.: MIMIC-CXR-JPG, a large publicly available database of labeled chest radiographs (2019). arXiv:1901.07042 [cs]"},{"key":"19_CR9","doi-asserted-by":"crossref","unstructured":"Li, M., Lin, B., Chen, Z., Lin, H., Liang, X., Chang, X.: Dynamic graph enhanced contrastive learning for chest x-ray report generation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 3334\u20133343 (2023)","DOI":"10.1109\/CVPR52729.2023.00325"},{"key":"19_CR10","unstructured":"Li, Y., Liang, X., Hu, Z., Xing, E.P.: Hybrid retrieval-generation reinforced agent for medical image report generation. Adv. Neural Inform. Process. Syst. 31 (2018)"},{"key":"19_CR11","unstructured":"Lin, C.-Y.: Rouge: a package for automatic evaluation of summaries. In: Text Summarization Branches Out, pp. 74\u201381 (2004)"},{"key":"19_CR12","doi-asserted-by":"crossref","unstructured":"Liu, F., Ren, X., Liu, Y., Lei, K., Sun, X.: Exploring and distilling cross-modal information for image captioning. arXiv preprint arXiv:2002.12585 (2020)","DOI":"10.24963\/ijcai.2019\/708"},{"key":"19_CR13","doi-asserted-by":"crossref","unstructured":"Liu, F., Yin, C., Wu, X., Ge, S., Zhang, P., Sun, X.: Contrastive attention for automatic chest x-ray report generation. In: Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021, pp. 269\u2013280 (2021)","DOI":"10.18653\/v1\/2021.findings-acl.23"},{"key":"19_CR14","first-page":"16266","volume":"34","author":"F Liu","year":"2021","unstructured":"Liu, F., You, C., Xian, W., Ge, S., Sun, X.: Auto-encoding knowledge graph for unsupervised medical report generation. Adv. Neural Inform. Process. Syst. 34, 16266\u201316279 (2021)","journal-title":"Adv. Neural Inform. Process. Syst."},{"key":"19_CR15","unstructured":"Loshchilov, I., Hutter, F.: Decoupled weight decay regularization. arXiv preprint arXiv:1711.05101 (2017)"},{"key":"19_CR16","doi-asserted-by":"crossref","unstructured":"McDonald, R.J.: The effects of changes in utilization and technological advancements of cross-sectional imaging on radiologist workload. Acad. Radiol. 22(9), 1191\u20131198 (2015)","DOI":"10.1016\/j.acra.2015.05.007"},{"key":"19_CR17","doi-asserted-by":"crossref","unstructured":"Papineni, K., Roukos, S., Ward, T., Zhu, W.-J.: Bleu: a method for automatic evaluation of machine translation. In: Proceedings of the 40th Annual Meeting of the Association for Computational Linguistics, pp. 311\u2013318 (2002)","DOI":"10.3115\/1073083.1073135"},{"key":"19_CR18","unstructured":"Qin, Z., Yi, H., Lao, Q., Li, K.: Medical image understanding with pretrained vision language models: a comprehensive study. arXiv preprint arXiv:2209.15517 (2022)"},{"key":"19_CR19","doi-asserted-by":"crossref","unstructured":"Rubin, D.L.: Creating and curating a terminology for radiology: ontology modeling and analysis. J. Dig. Imag. 21(4):355\u2013362 (2008)","DOI":"10.1007\/s10278-007-9073-0"},{"key":"19_CR20","doi-asserted-by":"crossref","unstructured":"Tang, Y., Yuan, Y., Tao, F., Tang, M.: Cross-modal augmented transformer for automated medical report generation. IEEE J. Transl. Eng. Health Med. Publisher: IEEE (2025)","DOI":"10.1109\/JTEHM.2025.3536441"},{"key":"19_CR21","doi-asserted-by":"crossref","unstructured":"Tanida, T., M\u00fcller, P., Kaissis, G., Rueckert, D.: Interactive and explainable region-guided radiology report generation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 7433\u20137442 (2023)","DOI":"10.1109\/CVPR52729.2023.00718"},{"key":"19_CR22","doi-asserted-by":"crossref","unstructured":"Wang, X., Peng, Y., Lu, L., Lu, Z., Summers, R.M.: Tienet: text-image embedding network for common thorax disease classification and re porting in chest x-rays. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 9049\u20139058 (2018)","DOI":"10.1109\/CVPR.2018.00943"},{"key":"19_CR23","doi-asserted-by":"crossref","unstructured":"Xiang, Z., Cui, S., Shang, C., Jiang, J., Zhang, L.: Gmod: graph-driven momentum distillation framework with active perception of disease severity for radiology report generation. In: International Conference on Medical Image Computing and Computer-Assisted Intervention, pp. 295\u2013305. Springer (2024)","DOI":"10.1007\/978-3-031-72086-4_28"},{"key":"19_CR24","doi-asserted-by":"crossref","unstructured":"Xue, Y., et al.: Multimodal recurrent model with attention for automated radiology report generation. In: International Conference on Medical Image Computing and Computer-Assisted Intervention, pp. 457\u2013466. Springer (20180","DOI":"10.1007\/978-3-030-00928-1_52"},{"key":"19_CR25","doi-asserted-by":"crossref","unstructured":"Zhang, Y., Wang, X., Xu, Z., Yu, Q., Yuille, A., Xu, D.: When radiology report generation meets knowledge graph. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 34, Issue 07, pp. 12910\u201312917 (2020)","DOI":"10.1609\/aaai.v34i07.6989"},{"key":"19_CR26","doi-asserted-by":"crossref","unstructured":"Zhou, K., Yang, J., Loy, C.C., Liu, Z.: Learning to prompt for vision-language models. Int. J. Comput. Vis. 130(9), 2337\u20132348 (2022)","DOI":"10.1007\/s11263-022-01653-1"}],"container-title":["Lecture Notes in Computer Science","Advanced Intelligent Computing Technology and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-92-3495-0_19","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,14]],"date-time":"2026-07-14T06:11:09Z","timestamp":1784009469000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-92-3495-0_19"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7,15]]},"ISBN":["9789819234943","9789819234950"],"references-count":26,"URL":"https:\/\/doi.org\/10.1007\/978-981-92-3495-0_19","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,7,15]]},"assertion":[{"value":"15 July 2026","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICIC","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Intelligent Computing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Toronto","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Canada","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2026","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22 July 2026","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"26 July 2026","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icic2026a","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.ic-icc.cn\/2026\/index.htm","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}