{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,2]],"date-time":"2026-01-02T03:05:33Z","timestamp":1767323133381,"version":"3.48.0"},"publisher-location":"Cham","reference-count":24,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783032139603","type":"print"},{"value":"9783032139610","type":"electronic"}],"license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"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\/978-3-032-13961-0_21","type":"book-chapter","created":{"date-parts":[[2026,1,2]],"date-time":"2026-01-02T03:01:48Z","timestamp":1767322908000},"page":"205-214","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Continual Multiple Instance Learning for\u00a0Hematologic Disease Diagnosis"],"prefix":"10.1007","author":[{"given":"Zahra","family":"Ebrahimi","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Raheleh","family":"Salehi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nassir","family":"Navab","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Carsten","family":"Marr","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ario","family":"Sadafi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2026,1,2]]},"reference":[{"key":"21_CR1","doi-asserted-by":"crossref","unstructured":"Bagus, B., Gepperth, A.: An investigation of replay-based approaches for continual learning. In: 2021 International Joint Conference on Neural Networks (IJCNN), pp.\u00a01\u20139. IEEE (2021)","DOI":"10.1109\/IJCNN52387.2021.9533862"},{"issue":"8","key":"21_CR2","doi-asserted-by":"publisher","first-page":"1301","DOI":"10.1038\/s41591-019-0508-1","volume":"25","author":"G Campanella","year":"2019","unstructured":"Campanella, G., et al.: Clinical-grade computational pathology using weakly supervised deep learning on whole slide images. Nat. Med. 25(8), 1301\u20131309 (2019)","journal-title":"Nat. Med."},{"key":"21_CR3","doi-asserted-by":"crossref","unstructured":"Chaudhry, A., Rohrbach, M., Elhoseiny, M., Ajanthan, T., Torr, P.H.: Riemannian walk for incremental learning: understanding forgetting and intransigence. In: Proceedings of the European Conference on Computer Vision (ECCV), pp. 532\u2013547 (2018)","DOI":"10.1007\/978-3-030-01252-6_33"},{"key":"21_CR4","doi-asserted-by":"publisher","first-page":"1045","DOI":"10.1007\/s10278-013-9622-7","volume":"26","author":"K Clark","year":"2013","unstructured":"Clark, K., et al.: The cancer imaging archive (tcia): maintaining and operating a public information repository. J. Digit. Imaging 26, 1045\u20131057 (2013)","journal-title":"J. Digit. Imaging"},{"key":"21_CR5","volume-title":"Introduction to Algorithms","author":"TH Cormen","year":"2001","unstructured":"Cormen, T.H., Leiserson, C.E., Rivest, R.L., Stein, C.: Introduction to Algorithms, 2nd edn. The MIT Press, Cambridge (2001)","edition":"2"},{"key":"21_CR6","doi-asserted-by":"crossref","unstructured":"Derakhshani, M.M., et al.: Lifelonger: a benchmark for continual disease classification. In: Medical Image Computing and Computer Assisted Intervention\u2013MICCAI 2022: 25th International Conference, Singapore, 18\u201322 September 2022, Proceedings, Part II, pp. 314\u2013324. Springer, Cham (2022)","DOI":"10.1007\/978-3-031-16434-7_31"},{"issue":"1","key":"21_CR7","doi-asserted-by":"publisher","first-page":"111","DOI":"10.1038\/s41375-021-01408-w","volume":"36","author":"JN Eckardt","year":"2022","unstructured":"Eckardt, J.N., et al.: Deep learning detects acute myeloid leukemia and predicts npm1 mutation status from bone marrow smears. Leukemia 36(1), 111\u2013118 (2022)","journal-title":"Leukemia"},{"issue":"1","key":"21_CR8","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s12885-022-09307-8","volume":"22","author":"JN Eckardt","year":"2022","unstructured":"Eckardt, J.N., et al.: Deep learning identifies acute promyelocytic leukemia in bone marrow smears. BMC Cancer 22(1), 1\u201311 (2022)","journal-title":"BMC Cancer"},{"issue":"3","key":"21_CR9","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pdig.0000187","volume":"2","author":"M Hehr","year":"2023","unstructured":"Hehr, M., et al.: Explainable AI identifies diagnostic cells of genetic AML subtypes. PLOS Digit. Health 2(3), e0000187 (2023). https:\/\/doi.org\/10.1371\/journal.pdig.0000187","journal-title":"PLOS Digit. Health"},{"key":"21_CR10","doi-asserted-by":"crossref","unstructured":"Kemker, R., McClure, M., Abitino, A., Hayes, T., Kanan, C.: Measuring catastrophic forgetting in neural networks. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol.\u00a032 (2018)","DOI":"10.1609\/aaai.v32i1.11651"},{"issue":"13","key":"21_CR11","doi-asserted-by":"publisher","first-page":"3521","DOI":"10.1073\/pnas.1611835114","volume":"114","author":"J Kirkpatrick","year":"2017","unstructured":"Kirkpatrick, J., et al.: Overcoming catastrophic forgetting in neural networks. Proc. Natl. Acad. Sci. 114(13), 3521\u20133526 (2017)","journal-title":"Proc. Natl. Acad. Sci."},{"issue":"5","key":"21_CR12","doi-asserted-by":"publisher","first-page":"775","DOI":"10.1038\/s41591-021-01343-4","volume":"27","author":"J Van der Laak","year":"2021","unstructured":"Van der Laak, J., Litjens, G., Ciompi, F.: Deep learning in histopathology: the path to the clinic. Nat. Med. 27(5), 775\u2013784 (2021)","journal-title":"Nat. Med."},{"key":"21_CR13","unstructured":"Matek, C., Schwarz, S., Marr, C., Spiekermann, K.: A single-cell morphological dataset of leukocytes from AML patients and non-malignant controls (aml-cytomorphology_lmu). The Cancer Imaging Archive (TCIA) (2019)"},{"issue":"11","key":"21_CR14","doi-asserted-by":"publisher","first-page":"538","DOI":"10.1038\/s42256-019-0101-9","volume":"1","author":"C Matek","year":"2019","unstructured":"Matek, C., Schwarz, S., Spiekermann, K., Marr, C.: Human-level recognition of blast cells in acute myeloid leukaemia with convolutional neural networks. Nat. Mach. Intell. 1(11), 538\u2013544 (2019)","journal-title":"Nat. Mach. Intell."},{"issue":"1","key":"21_CR15","doi-asserted-by":"publisher","first-page":"486","DOI":"10.1112\/plms\/s1-28.1.486","volume":"1","author":"GB Mathews","year":"1896","unstructured":"Mathews, G.B.: On the partition of numbers. Proc. Lond. Math. Soc. 1(1), 486\u2013490 (1896)","journal-title":"Proc. Lond. Math. Soc."},{"key":"21_CR16","doi-asserted-by":"publisher","DOI":"10.1016\/j.artmed.2024.102870","volume":"152","author":"P Meseguer","year":"2024","unstructured":"Meseguer, P., Del Amor, R., Naranjo, V.: Micil: multiple-instance class-incremental learning for skin cancer whole slide images. Artif. Intell. Med. 152, 102870 (2024)","journal-title":"Artif. Intell. Med."},{"key":"21_CR17","doi-asserted-by":"crossref","unstructured":"Rebuffi, S.A., Kolesnikov, A., Sperl, G., Lampert, C.H.: icarl: incremental classifier and representation learning. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 2001\u20132010 (2017)","DOI":"10.1109\/CVPR.2017.587"},{"key":"21_CR18","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"246","DOI":"10.1007\/978-3-030-59722-1_24","volume-title":"Medical Image Computing and Computer Assisted Intervention \u2013 MICCAI 2020","author":"A Sadafi","year":"2020","unstructured":"Sadafi, A., et al.: Attention based multiple instance learning for classification of blood cell disorders. In: Martel, A.L., et al. (eds.) MICCAI 2020. LNCS, vol. 12265, pp. 246\u2013256. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-59722-1_24"},{"key":"21_CR19","doi-asserted-by":"crossref","unstructured":"Sadafi, A., et al.: A continual learning approach for cross-domain white blood cell classification. In: MICCAI Workshop on Domain Adaptation and Representation Transfer, pp. 136\u2013146. Springer, Cham (2023)","DOI":"10.1007\/978-3-031-45857-6_14"},{"key":"21_CR20","doi-asserted-by":"crossref","unstructured":"Salehi, R., et al.: Unsupervised cross-domain feature extraction for single blood cell image classification. In: Medical Image Computing and Computer Assisted Intervention\u2013MICCAI 2022: 25th International Conference, Singapore, 18\u201322 September 2022, Proceedings, Part III, pp. 739\u2013748. Springer, Cham (2022)","DOI":"10.1007\/978-3-031-16437-8_71"},{"issue":"1","key":"21_CR21","doi-asserted-by":"publisher","first-page":"38","DOI":"10.1038\/s41698-021-00179-y","volume":"5","author":"JW Sidhom","year":"2021","unstructured":"Sidhom, J.W., et al.: Deep learning for diagnosis of acute promyelocytic leukemia via recognition of genomically imprinted morphologic features. NPJ Precis. Oncol. 5(1), 38 (2021)","journal-title":"NPJ Precis. Oncol."},{"key":"21_CR22","doi-asserted-by":"crossref","unstructured":"Wu, Y., et al.: Large scale incremental learning. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 374\u2013382 (2019)","DOI":"10.1109\/CVPR.2019.00046"},{"key":"21_CR23","doi-asserted-by":"crossref","unstructured":"Xie, S., Girshick, R., Doll\u00e1r, P., Tu, Z., He, K.: Aggregated residual transformations for deep neural networks. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1492\u20131500 (2017)","DOI":"10.1109\/CVPR.2017.634"},{"key":"21_CR24","doi-asserted-by":"crossref","unstructured":"Yan, S., Xie, J., He, X.: Der: dynamically expandable representation for class incremental learning. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 3014\u20133023 (2021)","DOI":"10.1109\/CVPR46437.2021.00303"}],"container-title":["Lecture Notes in Computer Science","Efficient Medical Artificial Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-032-13961-0_21","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,2]],"date-time":"2026-01-02T03:01:49Z","timestamp":1767322909000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-032-13961-0_21"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026]]},"ISBN":["9783032139603","9783032139610"],"references-count":24,"URL":"https:\/\/doi.org\/10.1007\/978-3-032-13961-0_21","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026]]},"assertion":[{"value":"2 January 2026","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"The authors have no competing interests to declare that are relevant to the content of this article.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Disclosure of Interests"}},{"value":"EMA4MICCAI 2025","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Workshop on Efficient Medical Artificial Intelligence","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Daejeon","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Korea (Republic of)","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":"23 September 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"23 September 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"1","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ema4miccai2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/sites.google.com\/view\/ema4miccai2025","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}