{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,27]],"date-time":"2026-03-27T08:58:10Z","timestamp":1774601890746,"version":"3.50.1"},"publisher-location":"Cham","reference-count":22,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031720857","type":"print"},{"value":"9783031720864","type":"electronic"}],"license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"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":[[2024]]},"DOI":"10.1007\/978-3-031-72086-4_41","type":"book-chapter","created":{"date-parts":[[2024,10,3]],"date-time":"2024-10-03T20:34:45Z","timestamp":1727987685000},"page":"437-446","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["Longitudinal Mammogram Risk Prediction"],"prefix":"10.1007","author":[{"given":"Batuhan K.","family":"Karaman","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Katerina","family":"Dodelzon","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gozde B.","family":"Akar","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mert R.","family":"Sabuncu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,10,4]]},"reference":[{"key":"41_CR1","doi-asserted-by":"publisher","unstructured":"Arasu, V.A., Habel, L.A., Achacoso, N., Buist, D.S., Cord, J.B., Esserman, L.J., Hylton, N.M., Glymour, M.M., Kornak, J., Kushi, L.H., Lewis, D.A., Vincent, J.L., Lydon, C., Miglioretti, D.L., Navarro, D., Pu, A.X., Shen, L., Sieh, W., Yoon, H.C., Lee, C.: Comparison of mammography ai algorithms with a clinical risk model for 5-year breast cancer risk prediction: An observational study. Radiology 307 (06 2023). https:\/\/doi.org\/10.1148\/radiol.222733","DOI":"10.1148\/radiol.222733"},{"key":"41_CR2","doi-asserted-by":"publisher","unstructured":"Dadsetan, S., Arefan, D., Berg, W.A., Zuley, M.L., Sumkin, J.H., Wu, S.: Deep learning of longitudinal mammogram examinations for breast cancer risk prediction. Pattern Recognition 132, 108919\u2013108919 (12 2022).https:\/\/doi.org\/10.1016\/j.patcog.2022.108919","DOI":"10.1016\/j.patcog.2022.108919"},{"key":"41_CR3","doi-asserted-by":"publisher","unstructured":"Damiani, C., Kalliatakis, G., Sreenivas, M., Al-Attar, M., Rose, J., Pudney, C., Lane, E.F., Cuzick, J., Montana, G., Brentnall, A.R.: Evaluation of an ai model to assess future breast cancer risk. Radiology 307 (06 2023).https:\/\/doi.org\/10.1148\/radiol.222679","DOI":"10.1148\/radiol.222679"},{"key":"41_CR4","doi-asserted-by":"publisher","unstructured":"Dembrower, K., Lindholm, P., Strand, F.: A multi-million mammography image dataset and population-based screening cohort for the training and evaluation of deep neural networks-the cohort of screen-aged women (csaw). Journal of Digital Imaging 33, 408\u2013413 (09 2019).https:\/\/doi.org\/10.1007\/s10278-019-00278-0","DOI":"10.1007\/s10278-019-00278-0"},{"key":"41_CR5","unstructured":"Dosovitskiy, A., Beyer, L., Kolesnikov, A., Weissenborn, D., Zhai, X., Unterthiner, T., Dehghani, M., Minderer, M., Heigold, G., Gelly, S., et\u00a0al.: An image is worth 16x16 words: Transformers for image recognition at scale. arXiv preprint arXiv:2010.11929 (2020)"},{"key":"41_CR6","doi-asserted-by":"publisher","unstructured":"Gastounioti, A., Desai, S., Ahluwalia, V.S., Conant, E.F., Kontos, D.: Artificial intelligence in mammographic phenotyping of breast cancer risk: a narrative review. Breast Cancer Research 24 (02 2022).https:\/\/doi.org\/10.1186\/s13058-022-01509-z","DOI":"10.1186\/s13058-022-01509-z"},{"key":"41_CR7","doi-asserted-by":"publisher","unstructured":"He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) pp. 770\u2013778 (06 2016). https:\/\/doi.org\/10.1109\/cvpr.2016.90","DOI":"10.1109\/cvpr.2016.90"},{"key":"41_CR8","doi-asserted-by":"publisher","unstructured":"Karaman, B.K., Mormino, E.C., Sabuncu, M.R.: Machine learning based multi-modal prediction of future decline toward alzheimer\u2019s disease: An empirical study. PLOS ONE 17, e0277322 (11 2022).https:\/\/doi.org\/10.1371\/journal.pone.0277322","DOI":"10.1371\/journal.pone.0277322"},{"key":"41_CR9","unstructured":"Karolinska case-control dataset, https:\/\/data.europa.eu\/data\/datasets\/https-doi-org-10-5878-45vm-t798?locale=en"},{"key":"41_CR10","doi-asserted-by":"publisher","unstructured":"Kim, G., Bahl, M.: Assessing risk of breast cancer: A review of risk prediction models. Journal of Breast Imaging 3, 144\u2013155 (02 2021).https:\/\/doi.org\/10.1093\/jbi\/wbab001","DOI":"10.1093\/jbi\/wbab001"},{"key":"41_CR11","doi-asserted-by":"publisher","unstructured":"Kim, H., Lim, J., Kim, H.G., Lim, Y., Seo, B.K., Bae, M.S.: Deep learning analysis of mammography for breast cancer risk prediction in asian women. Diagnostics 13, \u00a02247 (01 2023). https:\/\/doi.org\/10.3390\/diagnostics13132247, https:\/\/www.mdpi.com\/2075-4418\/13\/13\/2247","DOI":"10.3390\/diagnostics13132247"},{"key":"41_CR12","doi-asserted-by":"publisher","unstructured":"Lee, H., Kim, J., Park, E., Kim, M., Kim, T., Kooi, T.: Enhancing breast cancer risk prediction by incorporating prior images. Lecture Notes in Computer Science pp. 389\u2013398 (01 2023). https:\/\/doi.org\/10.1007\/978-3-031-43904-9_38","DOI":"10.1007\/978-3-031-43904-9_38"},{"key":"41_CR13","doi-asserted-by":"publisher","unstructured":"Santeramo, R., Damiani, C., Wei, J., Montana, G., Brentnall, A.R.: Are better ai algorithms for breast cancer detection also better at predicting risk? a paired case-control study. Breast Cancer Research 26 (02 2024).https:\/\/doi.org\/10.1186\/s13058-024-01775-z","DOI":"10.1186\/s13058-024-01775-z"},{"key":"41_CR14","doi-asserted-by":"crossref","unstructured":"Selvaraju, R.R., Cogswell, M., Das, A., Vedantam, R., Parikh, D., Batra, D.: Grad-cam: Visual explanations from deep networks via gradient-based localization. In: Proceedings of the IEEE international conference on computer vision. pp. 618\u2013626 (2017)","DOI":"10.1109\/ICCV.2017.74"},{"key":"41_CR15","doi-asserted-by":"publisher","unstructured":"Tasci, E., Zhuge, Y., Camphausen, K., Krauze, A.V.: Bias and class imbalance in oncologic data-towards inclusive and transferrable ai in large scale oncology data sets. Cancers 14, \u00a02897 (06 2022).https:\/\/doi.org\/10.3390\/cancers14122897","DOI":"10.3390\/cancers14122897"},{"key":"41_CR16","unstructured":"Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A.N., Kaiser, L., Polosukhin, I.: Attention is all you need (2017)"},{"key":"41_CR17","doi-asserted-by":"publisher","unstructured":"Wilkinson, L., Gathani, T.: Understanding breast cancer as a global health concern. The British Journal of Radiology 95 (12 2021).https:\/\/doi.org\/10.1259\/bjr.20211033, https:\/\/www.ncbi.nlm.nih.gov\/pmc\/articles\/PMC8822551\/","DOI":"10.1259\/bjr.20211033"},{"key":"41_CR18","doi-asserted-by":"publisher","unstructured":"Yala, A., Lehman, C., Schuster, T., Portnoi, T., Barzilay, R.: A deep learning mammography-based model for improved breast cancer risk prediction. Radiology 292, 60\u201366 (07 2019). https:\/\/doi.org\/10.1148\/radiol.2019182716","DOI":"10.1148\/radiol.2019182716"},{"key":"41_CR19","doi-asserted-by":"publisher","unstructured":"Yala, A., Mikhael, P.G., Strand, F., Lin, G., Satuluru, S., Kim, T., Banerjee, I., Gichoya, J., Trivedi, H., Lehman, C.D., Hughes, K., Sheedy, D.J., Matthis, L.M., Karunakaran, B., Hegarty, K.E., Sabino, S., Silva, T.B., Evangelista, M.C., Caron, R.F., Souza, B., Mauad, E.C., Patalon, T., Handelman-Gotlib, S., Guindy, M., Barzilay, R.: Multi-institutional validation of a mammography-based breast cancer risk model. Journal of Clinical Oncology (11 2022). https:\/\/doi.org\/10.1200\/jco.21.01337","DOI":"10.1200\/jco.21.01337"},{"key":"41_CR20","doi-asserted-by":"publisher","unstructured":"Yala, A., Mikhael, P.G., Strand, F., Lin, G., Smith, K., Wan, Y.L., Lamb, L., Hughes, K., Lehman, C., Barzilay, R.: Toward robust mammography-based models for breast cancer risk. Science Translational Medicine 13, eaba4373 (01 2021). https:\/\/doi.org\/10.1126\/scitranslmed.aba4373","DOI":"10.1126\/scitranslmed.aba4373"},{"key":"41_CR21","doi-asserted-by":"publisher","unstructured":"Yu, A.C., Eng, J.: One algorithm may not fit all: How selection bias affects machine learning performance. RadioGraphics p. 200040 (09 2020).https:\/\/doi.org\/10.1148\/rg.2020200040","DOI":"10.1148\/rg.2020200040"},{"key":"41_CR22","doi-asserted-by":"publisher","unstructured":"Yuan, W., Beaulieu-Jones, B.K., Yu, K.H., Lipnick, S.L., Palmer, N., Loscalzo, J., Cai, T., Kohane, I.S.: Temporal bias in case-control design: preventing reliable predictions of the future. Nature Communications 12 (02 2021). https:\/\/doi.org\/10.1038\/s41467-021-21390-2","DOI":"10.1038\/s41467-021-21390-2"}],"container-title":["Lecture Notes in Computer Science","Medical Image Computing and Computer Assisted Intervention \u2013 MICCAI 2024"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-72086-4_41","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,3]],"date-time":"2024-10-03T20:39:28Z","timestamp":1727987968000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-72086-4_41"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9783031720857","9783031720864"],"references-count":22,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-72086-4_41","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"4 October 2024","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":"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":"Marrakesh","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Morocco","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"7 October 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"11 October 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"miccai2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/conferences.miccai.org\/2024\/en\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}