{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,2]],"date-time":"2026-07-02T19:38:56Z","timestamp":1783021136762,"version":"3.54.6"},"publisher-location":"Cham","reference-count":24,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783032045546","type":"print"},{"value":"9783032045553","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,9,12]],"date-time":"2025-09-12T00:00:00Z","timestamp":1757635200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,9,12]],"date-time":"2025-09-12T00:00:00Z","timestamp":1757635200000},"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":[[2026]]},"DOI":"10.1007\/978-3-032-04555-3_34","type":"book-chapter","created":{"date-parts":[[2025,9,11]],"date-time":"2025-09-11T08:55:38Z","timestamp":1757580938000},"page":"415-427","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A Classification Algorithm for\u00a0Bronchiolitis Obliterans in\u00a0Pediatric CT Images with\u00a0Extreme Class Imbalance"],"prefix":"10.1007","author":[{"given":"Lu","family":"Liu","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xibin","family":"Feng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ye","family":"Yuan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wei","family":"Xu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wenjun","family":"Tan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,9,12]]},"reference":[{"issue":"5","key":"34_CR1","doi-asserted-by":"publisher","first-page":"481","DOI":"10.1080\/17476348.2019.1586537","volume":"13","author":"E Kavaliunaite","year":"2019","unstructured":"Kavaliunaite, E., Aurora, P.: Diagnosing and managing bronchiolitis obliterans in children. Expert Rev. Respir. Med. 13(5), 481\u2013488 (2019)","journal-title":"Expert Rev. Respir. Med."},{"issue":"12","key":"34_CR2","doi-asserted-by":"publisher","first-page":"459","DOI":"10.3345\/kjp.2015.58.12.459","volume":"58","author":"J Yu","year":"2015","unstructured":"Yu, J.: Postinfectious bronchiolitis obliterans in children: lessons from bronchiolitis obliterans after lung transplantation and hematopoietic stem cell transplantation. Korean J. Pediatr. 58(12), 459 (2015)","journal-title":"Korean J. Pediatr."},{"issue":"1","key":"34_CR3","doi-asserted-by":"publisher","first-page":"156","DOI":"10.1016\/j.cyto.2014.10.026","volume":"73","author":"M Rosewich","year":"2015","unstructured":"Rosewich, M., Zissler, U.M., Kheiri, T., et al.: Airway inflammation in children and adolescents with bronchiolitis obliterans. Cytokine 73(1), 156\u2013162 (2015)","journal-title":"Cytokine"},{"issue":"1","key":"34_CR4","doi-asserted-by":"publisher","first-page":"153","DOI":"10.1002\/ppul.25166","volume":"56","author":"KC Chan","year":"2021","unstructured":"Chan, K.C., Yu, M.W., Cheung, T.W.Y., et al.: Childhood bronchiolitis obliterans in Hong Kong-case series over a 20-year period. Pediatr. Pulmonol. 56(1), 153\u2013161 (2021)","journal-title":"Pediatr. Pulmonol."},{"issue":"1","key":"34_CR5","first-page":"5852827","volume":"2020","author":"SP Jerkic","year":"2020","unstructured":"Jerkic, S.P., Brinkmann, F., Calder, A., et al.: Postinfectious bronchiolitis obliterans in children: diagnostic workup and therapeutic options: a workshop report. Can. Respir. J. 2020(1), 5852827 (2020)","journal-title":"Can. Respir. J."},{"key":"34_CR6","doi-asserted-by":"publisher","first-page":"1281922","DOI":"10.3389\/fonc.2024.1281922","volume":"14","author":"L Wang","year":"2024","unstructured":"Wang, L.: Mammography with deep learning for breast cancer detection. Front. Oncol. 14, 1281922 (2024)","journal-title":"Front. Oncol."},{"issue":"22","key":"34_CR7","doi-asserted-by":"publisher","first-page":"32643","DOI":"10.1007\/s11042-022-13081-x","volume":"81","author":"W Salma","year":"2022","unstructured":"Salma, W., Eltrass, A.S.: Automated deep learning approach for classification of malignant melanoma and benign skin lesions. Multimedia Tools Appl. 81(22), 32643\u201332660 (2022)","journal-title":"Multimedia Tools Appl."},{"key":"34_CR8","doi-asserted-by":"crossref","unstructured":"Sangeetha, K., Valarmathi, K., Kalaichelvi, T., et al.: A broad study of machine learning and deep learning techniques for diabetic retinopathy based on feature extraction, detection and classification. Measur. Sens. 30, 100951 (2023)","DOI":"10.1016\/j.measen.2023.100951"},{"key":"34_CR9","doi-asserted-by":"crossref","unstructured":"Gong, D., Kras, A., Miller, J.B.: Application of deep learning for diagnosing, classifying, and treating age-related macular degeneration. In: Seminars in Ophthalmology. Taylor & Francis vol. 36. no. 4, pp. 198\u2013204 (2021)","DOI":"10.1080\/08820538.2021.1889617"},{"key":"34_CR10","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2021.104348","volume":"132","author":"DM Ibrahim","year":"2021","unstructured":"Ibrahim, D.M., Elshennawy, N.M., Sarhan, A.M.: Deep-chest: multi-classification deep learning model for diagnosing COVID-19, pneumonia, and lung cancer chest diseases. Comput. Biol. Med. 132, 104348 (2021)","journal-title":"Comput. Biol. Med."},{"key":"34_CR11","doi-asserted-by":"crossref","unstructured":"Szegedy, C., Liu, W., Jia, Y., et al.: Going deeper with convolutions. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1\u20139 (2015)","DOI":"10.1109\/CVPR.2015.7298594"},{"key":"34_CR12","doi-asserted-by":"crossref","unstructured":"Szegedy, C., Vanhoucke, V., Ioffe, S., et al.: Rethinking the inception architecture for computer vision. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 2818\u20132826 (2016)","DOI":"10.1109\/CVPR.2016.308"},{"key":"34_CR13","doi-asserted-by":"crossref","unstructured":"Szegedy, C., Ioffe, S., Vanhoucke, V., et al.: Inception-v4, inception-ResNet and the impact of residual connections on learning. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 31, no. 1 (2017)","DOI":"10.1609\/aaai.v31i1.11231"},{"issue":"1","key":"34_CR14","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s40537-019-0192-5","volume":"6","author":"JM Johnson","year":"2019","unstructured":"Johnson, J.M., Khoshgoftaar, T.M.: Survey on deep learning with class imbalance. J. Big Data 6(1), 1\u201354 (2019)","journal-title":"J. Big Data"},{"key":"34_CR15","unstructured":"Clevert, D.A.: Fast and accurate deep network learning by exponential linear units (elus). arxiv preprint arxiv:1511.07289 (2015)"},{"key":"34_CR16","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2022.105151","volume":"115","author":"MA Ganaie","year":"2022","unstructured":"Ganaie, M.A., Hu, M., Malik, A.K., et al.: Ensemble deep learning: a review. Eng. Appl. Artif. Intell. 115, 105151 (2022)","journal-title":"Eng. Appl. Artif. Intell."},{"key":"34_CR17","doi-asserted-by":"crossref","unstructured":"He, K., Zhang, X., Ren, S., et al.: Deep residual learning for image recognition. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 770\u2013778 (2016)","DOI":"10.1109\/CVPR.2016.90"},{"key":"34_CR18","doi-asserted-by":"crossref","unstructured":"Huang, G., Liu, Z., Van Der Maaten, L., et al.: Densely connected convolutional networks. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 4700\u20134708 (2017)","DOI":"10.1109\/CVPR.2017.243"},{"key":"34_CR19","unstructured":"Tan, M., Le, Q.: EfficientNet: rethinking model scaling for convolutional neural networks. In: International Conference on Machine Learning. PMLR, pp. 6105\u20136114 (2019)"},{"key":"34_CR20","unstructured":"Dosovitskiy, A.: An image is worth 16x16 words: Transformers for image recognition at scale. arxiv preprint arxiv:2010.11929 (2020)"},{"key":"34_CR21","doi-asserted-by":"crossref","unstructured":"Liu, Z., Lin, Y., Cao, Y., et al.: Swin transformer: hierarchical vision transformer using shifted windows. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 10012\u201310022 (2021)","DOI":"10.1109\/ICCV48922.2021.00986"},{"key":"34_CR22","doi-asserted-by":"crossref","unstructured":"Liu, Z., Mao, H., Wu, C.Y., et al.: A convnet for the 2020s. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 11976\u201311986 (2022)","DOI":"10.1109\/CVPR52688.2022.01167"},{"key":"34_CR23","doi-asserted-by":"crossref","unstructured":"Cai, H., Li, J., Hu, M., et al.: EfficientViT: lightweight multi-scale attention for high-resolution dense prediction. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 17302\u201317313 (2023)","DOI":"10.1109\/ICCV51070.2023.01587"},{"key":"34_CR24","doi-asserted-by":"crossref","unstructured":"Qin, D., Leichner, C., Delakis, M., et al.: MobileNetV4: universal models for the mobile ecosystem. In: European Conference on Computer Vision. Springer, Cham, pp. 78\u201396 (2025)","DOI":"10.1007\/978-3-031-73661-2_5"}],"container-title":["Lecture Notes in Computer Science","Artificial Neural Networks and Machine Learning \u2013 ICANN 2025"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-032-04555-3_34","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,2]],"date-time":"2026-07-02T18:44:35Z","timestamp":1783017875000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-032-04555-3_34"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,9,12]]},"ISBN":["9783032045546","9783032045553"],"references-count":24,"URL":"https:\/\/doi.org\/10.1007\/978-3-032-04555-3_34","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,9,12]]},"assertion":[{"value":"12 September 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICANN","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Artificial Neural Networks","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Kaunas","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Lithuania","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2025","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"9 September 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"12 September 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"34","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icann2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/e-nns.org\/icann2025\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}