{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T07:17:58Z","timestamp":1790839078547,"version":"4.1.0"},"publisher-location":"Cham","reference-count":20,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031439896","type":"print"},{"value":"9783031439902","type":"electronic"}],"license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"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":[[2023]]},"DOI":"10.1007\/978-3-031-43990-2_69","type":"book-chapter","created":{"date-parts":[[2023,9,30]],"date-time":"2023-09-30T23:07:48Z","timestamp":1696115268000},"page":"735-744","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Incomplete Multimodal Learning for\u00a0Visual Acuity Prediction After Cataract Surgery Using Masked Self-Attention"],"prefix":"10.1007","author":[{"given":"Qian","family":"Zhou","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hua","family":"Zou","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Haifeng","family":"Jiang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yong","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2023,10,1]]},"reference":[{"key":"69_CR1","doi-asserted-by":"crossref","unstructured":"Alexeeff, S.E., et al.: Development and validation of machine learning models: electronic health record data to predict visual acuity after cataract surgery. Perm. J. 25, 188 (2021)","DOI":"10.7812\/TPP\/20.188"},{"key":"69_CR2","doi-asserted-by":"crossref","unstructured":"An, J., Zhang, L., Wang, Y., Zhang, Z.: The success of cataract surgery and the preoperative measurement of retinal function by electrophysiological techniques. J. Ophthalmol. 2015, 401281 (2015)","DOI":"10.1155\/2015\/401281"},{"key":"69_CR3","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"213","DOI":"10.1007\/978-3-030-58452-8_13","volume-title":"Computer Vision \u2013 ECCV 2020","author":"N Carion","year":"2020","unstructured":"Carion, N., Massa, F., Synnaeve, G., Usunier, N., Kirillov, A., Zagoruyko, S.: End-to-end object detection with transformers. In: Vedaldi, A., Bischof, H., Brox, T., Frahm, J.-M. (eds.) ECCV 2020. LNCS, vol. 12346, pp. 213\u2013229. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-58452-8_13"},{"key":"69_CR4","unstructured":"Dosovitskiy, A., et al.: An image is worth 16x16 words: transformers for image recognition at scale. arXiv preprint arXiv:2010.11929 (2020)"},{"issue":"7","key":"69_CR5","doi-asserted-by":"publisher","first-page":"693","DOI":"10.1111\/aos.14430","volume":"98","author":"TRJ Forshaw","year":"2020","unstructured":"Forshaw, T.R.J., Ahmed, H.J., Kj\u00e6r, T.W., Andr\u00e9asson, S., S\u00f8rensen, T.L.: Full-field electroretinography in age-related macular degeneration: can retinal electrophysiology predict the subjective visual outcome of cataract surgery? Acta Ophthalmol. 98(7), 693\u2013700 (2020)","journal-title":"Acta Ophthalmol."},{"key":"69_CR6","unstructured":"Huang, Z., Lin, L., Cheng, P., Peng, L., Tang, X.: Multi-modal brain tumor segmentation via missing modality synthesis and modality-level attention fusion. arXiv preprint arXiv:2203.04586 (2022)"},{"key":"69_CR7","doi-asserted-by":"crossref","unstructured":"Ma, M., Ren, J., Zhao, L., Testuggine, D., Peng, X.: Are multimodal transformers robust to missing modality? In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 18177\u201318186 (2022)","DOI":"10.1109\/CVPR52688.2022.01764"},{"issue":"5","key":"69_CR8","doi-asserted-by":"publisher","first-page":"559","DOI":"10.5301\/ejo.5000993","volume":"27","author":"M Mimouni","year":"2017","unstructured":"Mimouni, M., Shapira, Y., Jadon, J., Frenkel, S., Blumenthal, E.Z.: Assessing visual function behind cataract: preoperative predictive value of the Heine lambda 100 Retinometer. Eur. J. Ophthalmol. 27(5), 559\u2013564 (2017)","journal-title":"Eur. J. Ophthalmol."},{"key":"69_CR9","unstructured":"Obata, S., et al.: Prediction of postoperative visual acuity after vitrectomy for macular hole using deep learning-based artificial intelligence. Graefe\u2019s Archive for Clinical and Experimental Ophthalmology, pp. 1\u201311 (2021)"},{"key":"69_CR10","unstructured":"Radford, A., et al.: Learning transferable visual models from natural language supervision. In: International Conference on Machine Learning, pp. 8748\u20138763. PMLR (2021)"},{"key":"69_CR11","doi-asserted-by":"crossref","unstructured":"Tharp, A., Cantor, L., Yung, C.W., Shoemaker, J.: Prospective comparison of the Heine Retinometer with the mentor Guyton-Minkowski potential acuity meter for the assessment of potential visual acuity before cataract surgery (1994)","DOI":"10.3928\/1542-8877-19940901-05"},{"key":"69_CR12","unstructured":"Vaswani, A., et al.: Attention is all you need. In: Advances in Neural Information Processing Systems 30 (2017)"},{"issue":"7","key":"69_CR13","doi-asserted-by":"publisher","first-page":"2283","DOI":"10.1007\/s00417-022-05605-w","volume":"260","author":"CS Wald","year":"2022","unstructured":"Wald, C.S., Unterlauft, J.D., Rehak, M., Girbardt, C.: Retinometer predicts visual outcome in Descemet membrane endothelial keratoplasty. Graefes Arch. Clin. Exp. Ophthalmol. 260(7), 2283\u20132290 (2022)","journal-title":"Graefes Arch. Clin. Exp. Ophthalmol."},{"key":"69_CR14","doi-asserted-by":"publisher","first-page":"1879","DOI":"10.1007\/s00417-021-05100-8","volume":"259","author":"H Wang","year":"2021","unstructured":"Wang, H., et al.: Electrophysiology as a prognostic indicator of visual recovery in diabetic patients undergoing cataract surgery. Graefes Arch. Clin. Exp. Ophthalmol. 259, 1879\u20131887 (2021)","journal-title":"Graefes Arch. Clin. Exp. Ophthalmol."},{"key":"69_CR15","doi-asserted-by":"crossref","unstructured":"Wang, J., et al.: CTT-Net: a multi-view cross-token transformer for cataract postoperative visual acuity prediction. In: 2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), pp. 835\u2013839. IEEE (2022)","DOI":"10.1109\/BIBM55620.2022.9995392"},{"key":"69_CR16","doi-asserted-by":"publisher","DOI":"10.3389\/fcell.2021.652848","volume":"9","author":"L WeiL","year":"2021","unstructured":"WeiL, L., et al.: An optical coherence tomography-based deep learning algorithm for visual acuity prediction of highly myopic eyes after cataract surgery. Front. Cell Develop. Biol. 9, 652848 (2021)","journal-title":"Front. Cell Develop. Biol."},{"key":"69_CR17","doi-asserted-by":"crossref","unstructured":"Xu, J., et al.: GroupViT: semantic segmentation emerges from text supervision. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 18134\u201318144 (2022)","DOI":"10.1109\/CVPR52688.2022.01760"},{"key":"69_CR18","doi-asserted-by":"publisher","unstructured":"Zhang, Y., et al.: mmFormer: multimodal medical transformer for incomplete multimodal learning of brain tumor segmentation. In: Wang, L., Dou, Q., Fletcher, P.T., Speidel, S., Li, S. (eds.) Medical Image Computing and Computer Assisted Intervention \u2013 MICCAI 2022. MICCAI 2022. LNCS, vol. 13435. Springer, Cham (2022). https:\/\/doi.org\/10.1007\/978-3-031-16443-9_11","DOI":"10.1007\/978-3-031-16443-9_11"},{"key":"69_CR19","doi-asserted-by":"crossref","unstructured":"Zhao, J., Li, R., Jin, Q.: Missing modality imagination network for emotion recognition with uncertain missing modalities. In: Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers), pp. 2608\u20132618 (2021)","DOI":"10.18653\/v1\/2021.acl-long.203"},{"key":"69_CR20","doi-asserted-by":"crossref","unstructured":"Zheng, S., et al.: Rethinking semantic segmentation from a sequence-to-sequence perspective with transformers. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 6881\u20136890 (2021)","DOI":"10.1109\/CVPR46437.2021.00681"}],"container-title":["Lecture Notes in Computer Science","Medical Image Computing and Computer Assisted Intervention \u2013 MICCAI 2023"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-43990-2_69","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,11]],"date-time":"2024-03-11T15:43:47Z","timestamp":1710171827000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-43990-2_69"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9783031439896","9783031439902"],"references-count":20,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-43990-2_69","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023]]},"assertion":[{"value":"1 October 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"MICCAI","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Medical Image Computing and Computer-Assisted Intervention","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Vancouver, BC","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":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8 October 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"12 October 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"miccai2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/conferences.miccai.org\/2023\/en\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"CMT","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"2250","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"730","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"32% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"5","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}