{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,6]],"date-time":"2026-03-06T07:35:32Z","timestamp":1772782532428,"version":"3.50.1"},"publisher-location":"Cham","reference-count":9,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783031082221","type":"print"},{"value":"9783031082238","type":"electronic"}],"license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022]]},"DOI":"10.1007\/978-3-031-08223-8_34","type":"book-chapter","created":{"date-parts":[[2022,6,14]],"date-time":"2022-06-14T14:11:04Z","timestamp":1655215864000},"page":"412-423","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Predicting Seriousness of\u00a0Injury in\u00a0a\u00a0Traffic Accident: A New Imbalanced Dataset and\u00a0Benchmark"],"prefix":"10.1007","author":[{"given":"Paschalis","family":"Lagias","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1884-0772","authenticated-orcid":false,"given":"George D.","family":"Magoulas","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9323-875X","authenticated-orcid":false,"given":"Ylli","family":"Prifti","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9542-4110","authenticated-orcid":false,"given":"Alessandro","family":"Provetti","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,6,10]]},"reference":[{"key":"34_CR1","unstructured":"Almohimeed, R.: UK traffic accidents - data analysis (10+years) (2019). https:\/\/medium.com\/@rawanme\/"},{"key":"34_CR2","doi-asserted-by":"publisher","unstructured":"Babi\u010d, F., Zusk\u00e1\u010dov\u00e1, K.: Descriptive and predictive mining on road accidents data. In: IEEE 14th International Symposium on Applied Machine Intelligence and Informatics (SAMI), pp. 87\u201392, January 2016. https:\/\/doi.org\/10.1109\/SAMI.2016.7422987","DOI":"10.1109\/SAMI.2016.7422987"},{"key":"34_CR3","doi-asserted-by":"publisher","first-page":"321","DOI":"10.1613\/jair.953","volume":"16","author":"NV Chawla","year":"2002","unstructured":"Chawla, N.V., Bowyer, K.W., Hall, L.O., Kegelmeyer, W.P.: SMOTE: synthetic minority over-sampling technique. J. Artif. Intell. Res. 16, 321\u2013357 (2002). https:\/\/doi.org\/10.1613\/jair.953","journal-title":"J. Artif. Intell. Res."},{"key":"34_CR4","doi-asserted-by":"crossref","unstructured":"Hasselt, H.v., Guez, A., Silver, D.: Deep reinforcement learning with double q-learning. In: Proceedings of the 30th AAAI Conference on Artificial Intelligence, pp. 2094\u20132100. AAAI 2016, AAAI Press (2016)","DOI":"10.1609\/aaai.v30i1.10295"},{"key":"34_CR5","doi-asserted-by":"publisher","unstructured":"Haynes, S., Estin, P.C., Lazarevski, S., Soosay, M., Kor, A.: Data analytics: Factors of traffic accidents in the UK. In: 10th International Conference on Dependable Systems, Services and Technologies, Leeds, United Kingdom, 5\u20137 June 2019, pp. 120\u2013126. IEEE (2019). https:\/\/doi.org\/10.1109\/DESSERT.2019.8770021","DOI":"10.1109\/DESSERT.2019.8770021"},{"key":"34_CR6","doi-asserted-by":"publisher","unstructured":"Kumeda, B., Zhang, F., Zhou, F., Hussain, S., Almasri, A., Assefa, M.: Classification of road traffic accident data using machine learning algorithms. In: IEEE 11th International Conference on Communication Software and Networks (ICCSN), pp. 682\u2013687 (2019). https:\/\/doi.org\/10.1109\/ICCSN.2019.8905362","DOI":"10.1109\/ICCSN.2019.8905362"},{"issue":"8","key":"34_CR7","doi-asserted-by":"publisher","first-page":"2488","DOI":"10.1007\/s10489-020-01637-z","volume":"50","author":"E Lin","year":"2020","unstructured":"Lin, E., Chen, Q., Qi, X.: Deep reinforcement learning for imbalanced classification. Appl. Intell. 50(8), 2488\u20132502 (2020). https:\/\/doi.org\/10.1007\/s10489-020-01637-z","journal-title":"Appl. Intell."},{"key":"34_CR8","doi-asserted-by":"publisher","unstructured":"Stekhoven, D.J., B\u00fchlmann, P.: MissForest-non-parametric missing value imputation for mixed-type data. Bioinformatics 28(1), 112\u2013118 (2011). https:\/\/doi.org\/10.1093\/bioinformatics\/btr597","DOI":"10.1093\/bioinformatics\/btr597"},{"key":"34_CR9","unstructured":"Zychlinski, S.: The search for categorical correlation (2018). https:\/\/towardsdatascience.com\/"}],"container-title":["Communications in Computer and Information Science","Engineering Applications of Neural Networks"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-08223-8_34","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,2,8]],"date-time":"2023-02-08T05:37:51Z","timestamp":1675834671000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-08223-8_34"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783031082221","9783031082238"],"references-count":9,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-08223-8_34","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"value":"1865-0929","type":"print"},{"value":"1865-0937","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"10 June 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"EANN","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Engineering Applications of Neural Networks","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Chersonisos, Crete","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Greece","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17 June 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"20 June 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"23","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"eann2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/eannconf.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}