{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,22]],"date-time":"2025-11-22T11:23:46Z","timestamp":1763810626846,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":19,"publisher":"ACM","license":[{"start":{"date-parts":[[2021,7,14]],"date-time":"2021-07-14T00:00:00Z","timestamp":1626220800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,7,14]]},"DOI":"10.1145\/3472163.3472170","type":"proceedings-article","created":{"date-parts":[[2021,9,7]],"date-time":"2021-09-07T16:46:57Z","timestamp":1631033217000},"page":"292-296","source":"Crossref","is-referenced-by-count":14,"title":["Viral pneumonia images classification by Multiple Instance Learning: preliminary results"],"prefix":"10.1145","author":[{"given":"Ester","family":"Zumpano","sequence":"first","affiliation":[{"name":"University of Calabria, Italy"}]},{"given":"Antonio","family":"Fuduli","sequence":"additional","affiliation":[{"name":"University of Calabria, Italy"}]},{"given":"Eugenio","family":"Vocaturo","sequence":"additional","affiliation":[{"name":"University of Calabria, Italy"}]},{"given":"Matteo","family":"Avolio","sequence":"additional","affiliation":[{"name":"University of Calabria, Italy"}]}],"member":"320","published-online":{"date-parts":[[2021,9,7]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1080\/0952813X.2021.1908431"},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2021.3054484"},{"key":"e_1_3_2_1_3_1","unstructured":"S. Andrews I. Tsochantaridis and T. Hofmann. 2003. Support vector machines for multiple-instance learning. In Advances in Neural Information Processing Systems S.\u00a0Becker S.\u00a0Thrun and K.\u00a0Obermayer (Eds.). MIT Press Cambridge 561\u2013568.  S. Andrews I. Tsochantaridis and T. Hofmann. 2003. Support vector machines for multiple-instance learning. In Advances in Neural Information Processing Systems S.\u00a0Becker S.\u00a0Thrun and K.\u00a0Obermayer (Eds.). MIT Press Cambridge 561\u2013568."},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2015.2430935"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2018.2885852"},{"volume-title":"2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). 1615\u20131619","author":"Astorino A.","key":"e_1_3_2_1_6_1"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1007\/s12539-019-00341-y"},{"key":"e_1_3_2_1_8_1","article-title":"A semiproximal support vector machine approach for binary multiple instance learning","volume":"10","author":"Avolio M.","year":"2020","journal-title":"IEEE Transactions on Neural Networks and Learning Systems, DOI"},{"volume-title":"Proceedings KDD-2001: Knowledge discovery and data mining, F.\u00a0Provost and R.\u00a0Srikant (Eds.). ACM, 77\u201386","author":"Fung G.","key":"e_1_3_2_1_9_1"},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1007\/BF02579036"},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"crossref","unstructured":"F. Herrera S. Ventura R. Bello C. Cornelis A. Zafra D. S\u00e1nchez-Tarrag\u00f3 and S. Vluymans. 2016. Multiple instance learning: Foundations and algorithms. Springer International Publishing.  F. Herrera S. Ventura R. Bello C. Cornelis A. Zafra D. S\u00e1nchez-Tarrag\u00f3 and S. Vluymans. 2016. Multiple instance learning: Foundations and algorithms. Springer International Publishing.","DOI":"10.1007\/978-3-319-47759-6"},{"volume-title":"Deep-chest: Multi-classification deep learning model for diagnosing COVID-19, pneumonia, and lung cancer chest diseases. Computers in biology and medicine 132","year":"2021","author":"Ibrahim M.","key":"e_1_3_2_1_12_1"},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"crossref","unstructured":"S. Johri M. Goyal S. Jain M. Baranwal V. Kumar and R. Upadhyay. 2021. A novel machine learning-based analytical framework for automatic detection of COVID-19 using chest X-ray images. International Journal of Imaging Systems and Technology (2021). In press.  S. Johri M. Goyal S. Jain M. Baranwal V. Kumar and R. Upadhyay. 2021. A novel machine learning-based analytical framework for automatic detection of COVID-19 using chest X-ray images. International Journal of Imaging Systems and Technology (2021). In press.","DOI":"10.1002\/ima.22613"},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.bbe.2021.01.002"},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1056\/NEJMoa2001316"},{"key":"e_1_3_2_1_16_1","unstructured":"P. Mooney. [n.d.]. Chest X-ray images (pneumonia). https:\/\/www.kaggle.com\/paultimothymooney\/chest-xray-pneumonia.  P. Mooney. [n.d.]. Chest X-ray images (pneumonia). https:\/\/www.kaggle.com\/paultimothymooney\/chest-xray-pneumonia."},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1109\/RBME.2017.2651164"},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1148\/radiol.2020201754"},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10489-020-01867-1"}],"event":{"name":"IDEAS 2021: 25th International Database Engineering & Applications Symposium","acronym":"IDEAS 2021","location":"Montreal QC Canada"},"container-title":["25th International Database Engineering &amp; Applications Symposium"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3472163.3472170","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3472163.3472170","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T18:10:00Z","timestamp":1750183800000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3472163.3472170"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,7,14]]},"references-count":19,"alternative-id":["10.1145\/3472163.3472170","10.1145\/3472163"],"URL":"https:\/\/doi.org\/10.1145\/3472163.3472170","relation":{},"subject":[],"published":{"date-parts":[[2021,7,14]]}}}