{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,11]],"date-time":"2024-09-11T07:49:17Z","timestamp":1726040957417},"publisher-location":"Cham","reference-count":14,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030291952"},{"type":"electronic","value":"9783030291969"}],"license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019]]},"DOI":"10.1007\/978-3-030-29196-9_7","type":"book-chapter","created":{"date-parts":[[2019,8,12]],"date-time":"2019-08-12T13:03:33Z","timestamp":1565615013000},"page":"114-131","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Going Deeper into Colorectal Cancer Histopathology"],"prefix":"10.1007","author":[{"given":"Francesco","family":"Ponzio","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Enrico","family":"Macii","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Elisa","family":"Ficarra","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Santa","family":"Di Cataldo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2019,8,13]]},"reference":[{"key":"7_CR1","unstructured":"Virtual pathology at the university of leeds (2018). \n                    http:\/\/www.virtualpathology.leeds.ac.uk\/"},{"key":"7_CR2","volume-title":"ABC of Colorectal Cancer","author":"A Young","year":"2011","unstructured":"Young, A., Hobbs, R., Kerr, D.: ABC of Colorectal Cancer, 2nd edn. Wiley, Hoboken (2011)","edition":"2"},{"key":"7_CR3","unstructured":"Chollet, F., et al.: Keras (2015). \n                    https:\/\/github.com\/fchollet\/keras"},{"key":"7_CR4","doi-asserted-by":"publisher","first-page":"56","DOI":"10.1016\/j.csbj.2016.11.002","volume":"15","author":"S Cataldo Di","year":"2017","unstructured":"Di Cataldo, S., Ficarra, E.: Mining textural knowledge in biological images: applications, methods and trends. Comput. Struct. Biotechnol. J. 15, 56\u201367 (2017). \n                    https:\/\/doi.org\/10.1016\/j.csbj.2016.11.002","journal-title":"Comput. Struct. Biotechnol. J."},{"key":"7_CR5","series-title":"Springer Series in Statistics","doi-asserted-by":"publisher","first-page":"9","DOI":"10.1007\/978-0-387-84858-7_2","volume-title":"The Elements of Statistical Learning","author":"T Hastie","year":"2009","unstructured":"Hastie, T., Tibshirani, R., Friedman, J.: Overview of supervised learning. In: Hastie, T., Tibshirani, R., Friedman, J. (eds.) The Elements of Statistical Learning. SSS, pp. 9\u201341. Springer, New York (2009). \n                    https:\/\/doi.org\/10.1007\/978-0-387-84858-7_2"},{"issue":"1","key":"7_CR6","doi-asserted-by":"publisher","first-page":"29","DOI":"10.4103\/2153-3539.186902","volume":"7","author":"A Janowczyk","year":"2016","unstructured":"Janowczyk, A., Madabhushi, A.: Deep learning for digital pathology image analysis: a comprehensive tutorial with selected use cases. J. Pathol. Inform. 7(1), 29 (2016). \n                    https:\/\/doi.org\/10.4103\/2153-3539.186902","journal-title":"J. Pathol. Inform."},{"key":"7_CR7","doi-asserted-by":"publisher","first-page":"30","DOI":"10.4103\/jpi.jpi_34_17","volume":"8","author":"B Korbar","year":"2017","unstructured":"Korbar, B., et al.: Deep learning for classification of colorectal polyps on whole-slide images. J. Pathol. Inform. 8, 30 (2017). \n                    https:\/\/doi.org\/10.4103\/jpi.jpi_34_17","journal-title":"J. Pathol. Inform."},{"issue":"Nov","key":"7_CR8","first-page":"2579","volume":"9","author":"L Maaten Van der","year":"2008","unstructured":"Van der Maaten, L., Hinton, G.: Visualizing data using t-SNE. J. Mach. Learn. Res. 9(Nov), 2579\u20132605 (2008)","journal-title":"J. Mach. Learn. Res."},{"issue":"3","key":"7_CR9","first-page":"105","volume":"7","author":"AR Marley","year":"2016","unstructured":"Marley, A.R., Nan, H.: Epidemiology of colorectal cancer. Int. J. Mol. Epidemiol. Genet. 7(3), 105\u2013114 (2016)","journal-title":"Int. J. Mol. Epidemiol. Genet."},{"key":"7_CR10","doi-asserted-by":"publisher","unstructured":"Ponzio, F., Macii, E., Ficarra, E., Di Cataldo, S.: Colorectal cancer classification using deep convolutional networks - an experimental study. In: Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOIMAGING, vol. 2, pp. 58\u201366. INSTICC, SciTePress (2018). \n                    https:\/\/doi.org\/10.5220\/0006643100580066","DOI":"10.5220\/0006643100580066"},{"issue":"1","key":"7_CR11","doi-asserted-by":"publisher","first-page":"145","DOI":"10.1016\/S0893-6080(98)00116-6","volume":"12","author":"N Qian","year":"1999","unstructured":"Qian, N.: On the momentum term in gradient descent learning algorithms. Neural Netw. 12(1), 145\u2013151 (1999)","journal-title":"Neural Netw."},{"key":"7_CR12","unstructured":"Simonyan, K., Zisserman, A.: Very deep convolutional networks for large-scale image recognition. arXiv preprint \n                    arXiv:1409.1556\n                    \n                   (2014)"},{"issue":"1","key":"7_CR13","doi-asserted-by":"publisher","first-page":"9","DOI":"10.1186\/s40537-016-0043-6","volume":"3","author":"K Weiss","year":"2016","unstructured":"Weiss, K., Khoshgoftaar, T.M., Wang, D.: A survey of transfer learning. J. Big Data 3(1), 9 (2016). \n                    https:\/\/doi.org\/10.1186\/s40537-016-0043-6","journal-title":"J. Big Data"},{"issue":"2","key":"7_CR14","doi-asserted-by":"publisher","first-page":"289","DOI":"10.1007\/s00365-006-0663-2","volume":"26","author":"Y Yao","year":"2007","unstructured":"Yao, Y., Rosasco, L., Caponnetto, A.: On early stopping in gradient descent learning. Constr. Approx. 26(2), 289\u2013315 (2007)","journal-title":"Constr. Approx."}],"container-title":["Communications in Computer and Information Science","Biomedical Engineering Systems and Technologies"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-29196-9_7","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,8,12]],"date-time":"2019-08-12T13:08:31Z","timestamp":1565615311000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-29196-9_7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"ISBN":["9783030291952","9783030291969"],"references-count":14,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-29196-9_7","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"type":"print","value":"1865-0929"},{"type":"electronic","value":"1865-0937"}],"subject":[],"published":{"date-parts":[[2019]]},"assertion":[{"value":"13 August 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"BIOSTEC","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Joint Conference on Biomedical Engineering Systems and Technologies","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Funchal, Madeira","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Portugal","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2018","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"19 January 2018","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"21 January 2018","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"11","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"biostec2018","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/biostec.org\/?y=2018","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":"Primoris","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"299","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":"62","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":"79","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":"21% - 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":"4","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":"4","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":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}