{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,6]],"date-time":"2025-12-06T18:24:45Z","timestamp":1765045485954},"reference-count":50,"publisher":"Springer Science and Business Media LLC","issue":"6","license":[{"start":{"date-parts":[[2022,4,6]],"date-time":"2022-04-06T00:00:00Z","timestamp":1649203200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,4,6]],"date-time":"2022-04-06T00:00:00Z","timestamp":1649203200000},"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":["Med Biol Eng Comput"],"published-print":{"date-parts":[[2022,6]]},"DOI":"10.1007\/s11517-022-02526-y","type":"journal-article","created":{"date-parts":[[2022,4,6]],"date-time":"2022-04-06T16:07:37Z","timestamp":1649261257000},"page":"1569-1584","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Multiple instance learning for lung pathophysiological findings detection using CT scans"],"prefix":"10.1007","volume":"60","author":[{"given":"Julieta","family":"Frade","sequence":"first","affiliation":[]},{"given":"Tania","family":"Pereira","sequence":"additional","affiliation":[]},{"given":"Joana","family":"Morgado","sequence":"additional","affiliation":[]},{"given":"Francisco","family":"Silva","sequence":"additional","affiliation":[]},{"given":"Cl\u00e1udia","family":"Freitas","sequence":"additional","affiliation":[]},{"given":"Jos\u00e9","family":"Mendes","sequence":"additional","affiliation":[]},{"given":"Eduardo","family":"Negr\u00e3o","sequence":"additional","affiliation":[]},{"given":"Beatriz Flor","family":"de Lima","sequence":"additional","affiliation":[]},{"given":"Miguel Correia da","family":"Silva","sequence":"additional","affiliation":[]},{"given":"Ant\u00f3nio J.","family":"Madureira","sequence":"additional","affiliation":[]},{"given":"Isabel","family":"Ramos","sequence":"additional","affiliation":[]},{"given":"Jos\u00e9 Lu\u00eds","family":"Costa","sequence":"additional","affiliation":[]},{"given":"Venceslau","family":"Hespanhol","sequence":"additional","affiliation":[]},{"given":"Ant\u00f3nio","family":"Cunha","sequence":"additional","affiliation":[]},{"given":"H\u00e9lder P.","family":"Oliveira","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,4,6]]},"reference":[{"issue":"10053","key":"2526_CR1","doi-asserted-by":"publisher","first-page":"1459","DOI":"10.1016\/S0140-6736(16)31012-1","volume":"388","author":"GBD 2015 Mortality and Causes of Death Collaborators","year":"2016","unstructured":"GBD 2015 Mortality and Causes of Death Collaborators (2016) Global, regional, and national life expectancy, all-cause mortality, and cause-specific mortality for 249 causes of death, 1980?2015: a systematic analysis for the global burden of disease study 2015. The lancet 388(10053):1459\u20131544","journal-title":"The lancet"},{"key":"2526_CR2","unstructured":"World Health Organization. Global status report on noncommunicable diseases (2014) Number WHO\/NMH\/NVI\/15.1. World Health Organization, 2014"},{"key":"2526_CR3","doi-asserted-by":"crossref","unstructured":"Ostridge K, Wilkinson TMA (2016) Present and future utility of computed tomography scanning in the assessment and management of COPD. ISSN: 13993003","DOI":"10.1183\/13993003.00041-2016"},{"key":"2526_CR4","doi-asserted-by":"crossref","unstructured":"Pinheiro G, Pereira T, Dias C, Freitas C, Hespanhol V, Costa JL, Cunha A, Oliveira HP (2020) Identifying relationships between imaging phenotypes and lung cancer-related mutation status: EGFR and KRAS. Scientific Reports. ISSN: 20452322","DOI":"10.1101\/794123"},{"key":"2526_CR5","doi-asserted-by":"crossref","unstructured":"Gevaert O, Echegaray S, Khuong A, Hoang CD, Shrager JB, Jensen KC, Berry GJ, Guo H, Lau C, Plevritis SK, Rubin DL, Napel S, Leung AN (2017) Predictive radiogenomics modeling of EGFR mutation status in lung cancer. Scientific Reports. ISSN: 20452322","DOI":"10.1038\/srep41674"},{"key":"2526_CR6","unstructured":"Mayo Clinic: Diseases and Conditions. https:\/\/www.mayoclinic.org\/diseases-conditions\/. Last accessed on 04\/02\/2020"},{"issue":"4","key":"2526_CR7","doi-asserted-by":"publisher","first-page":"821","DOI":"10.1183\/09031936.00047908","volume":"33","author":"M Infante","year":"2009","unstructured":"Infante M, Lutman RF, Imparato S, Di Rocco M, Ceresoli GL, Torri V, Morenghi E, Minuti F, Cavuto S, Bottoni E, Inzirillo F, Cariboni U, Errico V, Incarbone MA, Ferraroli G, Brambilla G, Alloisio M, Ravasi G (2009) Differential diagnosis and management of focal ground-glass opacities. Europ Resp J 33(4):821\u2013827. ISSN: 09031936","journal-title":"Europ Resp J"},{"key":"2526_CR8","unstructured":"Lung Cancer Guide \u2014 What You Need to Know. https:\/\/www.cancer.org\/cancer\/lung-cancer. Last accessed on 23\/01\/2020"},{"key":"2526_CR9","unstructured":"Li C, Nie S, Wang Y, Sun X (2012) Experimental investigation of fuzzy enhancement for nonsolid pulmonary nodules. In: Proceedings - 2012 IEEE symposium on robotics and applications, ISRA 2012, pp 756\u2013759. ISBN 9781467322072"},{"key":"2526_CR10","doi-asserted-by":"crossref","unstructured":"Wang Z, Xu H, Sun M (2018) Deep learning based nodule detection from pulmonary CT images. In: Proceedings - 2017 10th international symposium on computational intelligence and design, ISCID 2017, volume 2018-January, pp 370\u2013373. Institute of Electrical and Electronics Engineers Inc. ISBN 9781538 636749","DOI":"10.1109\/ISCID.2017.107"},{"key":"2526_CR11","doi-asserted-by":"crossref","unstructured":"Bakr S, Gevaert O, Echegaray S, Ayers K, Zhou M, Shafiq M, Zheng H, Benson JA, Zhang W, Leung ANC, Kadoch M, Hoang CD, Shrager J, Quon A, Rubin DL, Sa K, Napel S (2018) Plevritis data descriptor: a radiogenomic dataset of non-small cell lung cancer. Scientific Data, 5. ISSN: 20524463","DOI":"10.1038\/sdata.2018.202"},{"key":"2526_CR12","doi-asserted-by":"crossref","unstructured":"Sharma SV, Bell DW, Settleman J, Haber DA (2007) Epidermal growth factor receptor mutations in lung cancer. ISSN: 1474175X","DOI":"10.1038\/nrc2088"},{"key":"2526_CR13","doi-asserted-by":"crossref","unstructured":"Jorge SEDC, Kobayashi SS, Costa DB (2014) Epidermal growth factor receptor (EGFR) mutations in lung cancer: preclinical and clinical data. ISSN: 16784510","DOI":"10.1590\/1414-431X20144099"},{"issue":"3","key":"2526_CR14","doi-asserted-by":"publisher","first-page":"260","DOI":"10.1111\/1759-7714.12436","volume":"8","author":"J Zou","year":"2017","unstructured":"Zou J, Lv T, S Zhu Z L u, Shen Q, L Xia J W u, Song Y, Liu H (2017) Computed tomography and clinical features associated with epidermal growth factor receptor mutation status in stage I\/II lung adenocarcinoma. Thoracic Cancer 8(3):260\u2013270. ISSN: 17597714","journal-title":"Thoracic Cancer"},{"key":"2526_CR15","doi-asserted-by":"crossref","unstructured":"Cheng Z, Shan F, Yang Y, Shi Y, Zhang Z (2017) CT characteristics of non-small cell lung cancer with epidermal growth factor receptor mutation: a systematic review and meta-analysis. BMC Medical Imaging, 17(1). ISSN: 14712342","DOI":"10.1186\/s12880-016-0175-3"},{"issue":"12","key":"2526_CR16","doi-asserted-by":"publisher","first-page":"6624","DOI":"10.21037\/jtd.2018.11.03","volume":"10","author":"XY Li","year":"2018","unstructured":"Li XY, Xiong JF, Jia TY, Shen TL, Hou RP, Zhao J, Fu XL (2018) Detection of epithelial growth factor receptor (EGFR) mutations on CT images of patients with lung adenocarcinoma using radiomics and\/or multi-level residual convolutionary neural networks. J Thor Dis 10(12):6624\u20136635. ISSN: 20776624","journal-title":"J Thor Dis"},{"issue":"2","key":"2526_CR17","doi-asserted-by":"publisher","first-page":"249","DOI":"10.1007\/s10147-017-1197-8","volume":"23","author":"Y Cao","year":"2018","unstructured":"Cao Y, Xu H, Liao M, Qu Y, Xu L, Zhu D, Wang B, Tian S (2018) Associations between clinical data and computed tomography features in patients with epidermal growth factor receptor mutations in lung adenocarcinoma. Int J Clinl Oncol 23(2):249\u2013257. ISSN: 14377772","journal-title":"Int J Clinl Oncol"},{"key":"2526_CR18","doi-asserted-by":"publisher","first-page":"148","DOI":"10.1016\/j.ejrad.2018.11.032","volume":"110","author":"S Rizzo","year":"2019","unstructured":"Rizzo S, Raimondi S, de Jong EEC, van Elmpt W, De Piano F, Petrella F, Bagnardi V, Jochems A, Bellomi M, Dingemans AM, Lambin P (2019) Genomics of non-small cell lung cancer (NSCLC): association between CT-based imaging features and EGFR and K-RAS mutations in 122 patients\u2014An external validation. Europ J Radiol 110:148\u2013155. ISSN: 18727727","journal-title":"Europ J Radiol"},{"key":"2526_CR19","doi-asserted-by":"crossref","unstructured":"Das A, Nair MS, Peter SD (2020) Computer-aided histopathological image analysis techniques for automated nuclear atypia scoring of breast cancer: a review. ISSN: 1618727X","DOI":"10.1007\/s10278-019-00295-z"},{"key":"2526_CR20","doi-asserted-by":"crossref","unstructured":"Safta W, Frigui H (2019) Multiple instance learning for benign vs. malignant classification of lung nodules in CT scans. In: 2018 IEEE International symposium on signal processing and information technology, ISSPIT 2018. ISBN 9781538675687","DOI":"10.1109\/ISSPIT.2018.8642791"},{"key":"2526_CR21","unstructured":"Asif A, Abbasi WA, Munir F, Ben-Hur A, ul Amir Afsar Minhas F (2017) pyLEMMINGS: large margin multiple instance classification and ranking for bioinformatics applications"},{"key":"2526_CR22","unstructured":"Zhou ZH, Sun YY, Li YF (2009) Multi-instance learning by treating instances as non-I.I.D. samples. In: ACM International conference proceeding series. ISBN 9781605585161, vol 382. ACM Press, New York, pp 1\u20138"},{"key":"2526_CR23","doi-asserted-by":"crossref","unstructured":"Doran G, Ray S (2014) A theoretical and empirical analysis of support vector machine methods for multiple-instance classification. In: Machine learning, vol 97, pp 79\u2013102. Kluwer Academic Publishers","DOI":"10.1007\/s10994-013-5429-5"},{"key":"2526_CR24","doi-asserted-by":"publisher","first-page":"329","DOI":"10.1016\/j.patcog.2017.10.009","volume":"77","author":"MA Carbonneau","year":"2018","unstructured":"Carbonneau MA, Cheplygina V, Granger E, Gagnon G (2018) Multiple instance learning: a survey of problem characteristics and applications. Pattern Recogn 77:329\u2013353. ISSN: 00313203","journal-title":"Pattern Recogn"},{"key":"2526_CR25","doi-asserted-by":"crossref","unstructured":"Cheplygina V, S\u00f8rensen L, Tax DMJ, Pedersen JH, Loog M, De Bruijne M (2014) Classification of COPD with multiple instance learning. In: Proceedings - international conference on pattern recognition. ISBN 9781479952083. Institute of Electrical and Electronics Engineers Inc., pp 1508\u20131513","DOI":"10.1109\/ICPR.2014.268"},{"key":"2526_CR26","unstructured":"Gang J, Yuan F, Bing Z (2013) Medical image semantic annotation based on MIL. In: 2013 ICME International conference on complex medical engineering, CME 2013. ISBN 9781467329699, pp 85\u201390"},{"key":"2526_CR27","unstructured":"Ramos J, Kockelkorn T, Van Ginneken B, Viergever MA, Grutters J, Ramos R, Campilho A (2013) Learning Interstitial Lung Diseases CT Patterns from Reports Keywords. Technical report"},{"key":"2526_CR28","doi-asserted-by":"publisher","first-page":"10","DOI":"10.1371\/journal.pone.0191600","volume":"13","author":"IP Pe\u00f1a","year":"2018","unstructured":"Pe\u00f1a IP, Cheplygina V, Paschaloudi S, Vuust M, Carl J, M\u00f8ller Weinreich U, \u00d8stergaard LR, de Bruijne M (2018) Automatic emphysema detection using weakly labeled HRCT lung images. Plos One 13:10","journal-title":"Plos One"},{"issue":"5","key":"2526_CR29","doi-asserted-by":"publisher","first-page":"486","DOI":"10.1109\/JBHI.2017.2769800","volume":"22","author":"V Cheplygina","year":"2018","unstructured":"Cheplygina V, Pena IP, Pedersen JH, Lynch DA, Sorensen L, De Bruijne M (2018) Transfer learning for multicenter classification of chronic obstructive pulmonary disease. IEEE J Biomed Health Inform 22(5):486\u20131496. ISSN: 21682194","journal-title":"IEEE J Biomed Health Inform"},{"key":"2526_CR30","doi-asserted-by":"crossref","unstructured":"Orting SN, Petersen J, Thomsen LH, Wille MMW, De Bruijne M (2018) Detecting emphysema with multiple instance learning. In: Proceedings - international symposium on biomedical imaging, volume 2018-April. ISBN 9781538636367. IEEE Computer Society, pp 510\u2013513","DOI":"10.1109\/ISBI.2018.8363627"},{"issue":"3","key":"2526_CR31","doi-asserted-by":"publisher","first-page":"227","DOI":"10.1016\/j.compmedimag.2011.07.003","volume":"36","author":"A Depeursinge","year":"2012","unstructured":"Depeursinge A, Vargas A, Platon A, Geissbuhler A, Poletti PA, M\u00fcller H (2012) Building a reference multimedia database for interstitial lung diseases. Comput Med Imag Graph 36(3):227\u2013238. ISSN: 08956111","journal-title":"Comput Med Imag Graph"},{"key":"2526_CR32","doi-asserted-by":"crossref","unstructured":"Park SH, Ha YG (2014) Large imbalance data classification based on MapReduce for traffic accident prediction. In: Proceedings - 2014 8th international conference on innovative mobile and internet services in ubiquitous computing, IMIS 2014, ISBN 9781479943319","DOI":"10.1109\/IMIS.2014.6"},{"key":"2526_CR33","doi-asserted-by":"crossref","unstructured":"Park Sh, Kim Sm, Ha Yg (2016) Highway traffic accident prediction using VDS big data analysis. Journal of Supercomputing. ISSN: 15730484","DOI":"10.1007\/s11227-016-1624-z"},{"key":"2526_CR34","doi-asserted-by":"crossref","unstructured":"Leevy JL, Khoshgoftaar TM, Bauder RA, Seliya N (2018) A survey on addressing high-class imbalance in big data. Journal of Big Data. ISSN: 21961115","DOI":"10.1186\/s40537-018-0151-6"},{"key":"2526_CR35","doi-asserted-by":"crossref","unstructured":"Rendon-Gonzalez E, Ponomaryov V (2016) Automatic Lung nodule segmentation and classification in CT images based on SVM. In: 9th International Kharkiv symposium on physics and engineering of microwaves, millimeter and submillimeter waves, MSMW 2016. Institute of Electrical and Electronics Engineers Inc., ISBN 9781509022663","DOI":"10.1109\/MSMW.2016.7537995"},{"issue":"3","key":"2526_CR36","doi-asserted-by":"publisher","first-page":"155","DOI":"10.1159\/000209296","volume":"87","author":"AO Hebb","year":"2009","unstructured":"Hebb AO, Poliakov AV (2009) Imaging of deep brain stimulation leads using extended hounsfield unit CT. Stereotactic and Functional Neurosurgery 87(3):155\u2013160. ISSN: 10116125","journal-title":"Stereotactic and Functional Neurosurgery"},{"key":"2526_CR37","doi-asserted-by":"crossref","unstructured":"Aresta GM (2016) Detection of juxta-pleural lung nodules in computed tomography images. Master\u2019s thesis. Faculdade de Engenharia da Universidade do Porto, 7","DOI":"10.1117\/12.2252022"},{"key":"2526_CR38","doi-asserted-by":"crossref","unstructured":"Bunescu RC, Mooney RJ (2007) Multiple instance learning for sparse positive bags. In: ACM International conference proceeding series, vol 227, pp 105\u2013112","DOI":"10.1145\/1273496.1273510"},{"key":"2526_CR39","unstructured":"G\u00e4rtner T, Flach PA, Kowalczyk AA, AlexSmola JS, Rsise A (2002) Multi-Instance Kernels. Technical report"},{"key":"2526_CR40","unstructured":"Zhou Z-H Multi-instance learning: a survey. Technical report"},{"key":"2526_CR41","unstructured":"Maron O, Ratan AL (1998) Multiple-instance learning for natural scene classiication"},{"issue":"2","key":"2526_CR42","doi-asserted-by":"publisher","first-page":"155","DOI":"10.1007\/s10994-016-5560-1","volume":"105","author":"XS Wei","year":"2016","unstructured":"Wei XS, Zhou ZH (2016) An empirical study on image bag generators for multi-instance learning. Mach Learn 105(2):155\u2013198. ISSN: 15730565","journal-title":"Mach Learn"},{"key":"2526_CR43","doi-asserted-by":"crossref","unstructured":"Zhu B, Luo W, Li B, Chen B, Yang Q, Xu Y, Wu X, Chen H, Zhang K (2014) The development and evaluation of a computerized diagnosis scheme for pneumoconiosis on digital chest radiographs. BioMedical Engineering Online. ISSN: 1475925X","DOI":"10.1186\/1475-925X-13-141"},{"key":"2526_CR44","doi-asserted-by":"crossref","unstructured":"El Ayachy R, Giraud N, Giraud P, Durdux C, Giraud P, Burgun A, Bibault JE (2021) The role of radiomics in lung cancer: from screening to treatment and follow-up. ISSN: 2234943X","DOI":"10.3389\/fonc.2021.603595"},{"issue":"21","key":"2526_CR45","doi-asserted-by":"publisher","first-page":"e104","DOI":"10.1158\/0008-5472.CAN-17-0339","volume":"77","author":"JJM Van Griethuysen","year":"2017","unstructured":"Van Griethuysen JJM, Fedorov A, Parmar C, Hosny A, Aucoin N, Narayan V, Beets-Tan RGH, Fillion-Robin JC, Pieper S, Aerts HJWL (2017) Computational radiomics system to decode the radiographic phenotype. Cancer Res 77(21):e104\u2013e107. ISSN: 15387445","journal-title":"Cancer Res"},{"key":"2526_CR46","unstructured":"DenOtter TD, Schubert J (2021) Hounsfield Unit. Treasure Island (FL): StatPearls Publishing"},{"key":"2526_CR47","doi-asserted-by":"crossref","unstructured":"Konkol M, \u015aniata\u0142a K, \u015aniata\u0142a P, Wilk S, Baczy\u0144ska B, Milecki P (2021) Computer tools to analyze lung CT changes after radiotherapy. Applied Sciences (Switzerland). ISSN: 20763417","DOI":"10.3390\/app11041582"},{"key":"2526_CR48","doi-asserted-by":"crossref","unstructured":"Mera C, Arrieta J, Orozco-Alzate M, Branch J (2015) A bag oversampling approach for class imbalance in multiple instance learning. In: Lecture notes in computer science (including subseries lecture notes in artificial intelligence and lecture notes in bioinformatics). ISBN 9783319257501, vol 9423. Springer, pp 724\u2013731","DOI":"10.1007\/978-3-319-25751-8_87"},{"key":"2526_CR49","unstructured":"Intro to Model Tuning: Grid and Random Search \u2014 Kaggle. https:\/\/www.kaggle.com\/willkoehrsen\/intro-to-model-tuning-grid-and-random-searchhttps:\/\/www.kaggle.com\/willkoehrsen\/intro-to-model-tuning-grid-and-random-search. Last accessed on 06\/06\/2020"},{"key":"2526_CR50","doi-asserted-by":"crossref","unstructured":"Pereira T, Freitas C, Costa JL, Morgado J, Silva F, Negr\u00e3o E, de Lima BF, da Silva MC, Madureira AJ, Ramos I, Hespanhol V, Cunha A, Oliveira HP (2020) Comprehensive Perspective for Lung Cancer Characterisation Based on AI Solutions Using CT Images. Journal of Clinical Medicine","DOI":"10.3390\/jcm10010118"}],"container-title":["Medical & Biological Engineering & Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11517-022-02526-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11517-022-02526-y\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11517-022-02526-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,7]],"date-time":"2022-05-07T06:29:05Z","timestamp":1651904945000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11517-022-02526-y"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,4,6]]},"references-count":50,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2022,6]]}},"alternative-id":["2526"],"URL":"https:\/\/doi.org\/10.1007\/s11517-022-02526-y","relation":{},"ISSN":["0140-0118","1741-0444"],"issn-type":[{"value":"0140-0118","type":"print"},{"value":"1741-0444","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,4,6]]},"assertion":[{"value":"26 May 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"17 January 2022","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"6 April 2022","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}