{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,8]],"date-time":"2026-09-08T00:32:28Z","timestamp":1788827548869,"version":"build-2803163510"},"reference-count":34,"publisher":"Springer Science and Business Media LLC","issue":"4","license":[{"start":{"date-parts":[[2020,4,24]],"date-time":"2020-04-24T00:00:00Z","timestamp":1587686400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,4,24]],"date-time":"2020-04-24T00:00:00Z","timestamp":1587686400000},"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":["J Digit Imaging"],"published-print":{"date-parts":[[2020,8]]},"DOI":"10.1007\/s10278-020-00337-x","type":"journal-article","created":{"date-parts":[[2020,4,24]],"date-time":"2020-04-24T13:03:38Z","timestamp":1587733418000},"page":"895-902","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":26,"title":["Prediction of Non-small Cell Lung Cancer Histology by a Deep Ensemble of Convolutional and Bidirectional Recurrent Neural Network"],"prefix":"10.1007","volume":"33","author":[{"given":"Dipanjan","family":"Moitra","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rakesh Kumar","family":"Mandal","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2020,4,24]]},"reference":[{"issue":"9","key":"337_CR1","doi-asserted-by":"publisher","first-page":"1681","DOI":"10.1093\/annonc\/mdu145","volume":"25","author":"KM Kerr","year":"2014","unstructured":"K. M. Kerr, L. Bubendorf, M. J. Edelman, A. Marchetti, T. Mok, S. Novello, K. O'Byrne, R. Stahel, S. Peters, E. Felip, Panel Members, Rolf Stahel, Enriqueta Felip, Solange Peters, Keith Kerr, Benjamin Besse, Johan Vansteenkiste, Wilfried Eberhardt, Martin Edelman, Tony Mok, Ken O'Byrne, Silvia Novello, Lukas Bubendorf, Antonio Marchetti, Paul Baas, Martin Reck, Konstantinos Syrigos, Luis Paz-Ares, Egbert F. Smit, Peter Meldgaard, Alex Adjei, Marianne Nicolson, Lucio Crin\u00f2, Paul Van Schil, Suresh Senan, Corinne Faivre-Finn, Gaetano Rocco, Giulia Veronesi, Jean-Yves Douillard, Eric Lim, Christophe Dooms, Walter Weder, Dirk De Ruysscher, Cecile De Pechoux, Paul De Leyn, Virginie Westeel, Second ESMO consensus conference on lung cancer: pathology and molecular biomarkers for non-small-cell lung cancer, Annals of Oncology, Volume 25, Issue 9, 2014, 1681\u20131690, https:\/\/doi.org\/10.1093\/annonc\/mdu145","journal-title":"Annals of Oncology"},{"key":"337_CR2","doi-asserted-by":"publisher","unstructured":"Wu Weimiao, Parmar Chintan, Grossmann Patrick, Quackenbush John, Lambin Philippe, Bussink Johan, Mak Raymond, Aerts Hugo J. W. L., Exploratory study to identify radiomics classifiers for lung cancer histology, Frontiers in Oncology, Volume 6, 2016, https:\/\/doi.org\/10.3389\/fonc.2016.00071","DOI":"10.3389\/fonc.2016.00071"},{"issue":"4","key":"337_CR3","doi-asserted-by":"publisher","first-page":"485","DOI":"10.1016\/j.jmoldx.2013.03.007","volume":"15","author":"MD Wilkerson","year":"2013","unstructured":"Matthew D. Wilkerson, Jason M. Schallheim, D. Neil Hayes, Patrick J. Roberts, Roy R.L. Bastien, Michael Mullins, Xiaoying Yin, C. Ryan Miller, Leigh B. Thorne, Katherine B. Geiersbach, Kenneth L. Muldrew, William K. Funkhouser, Cheng Fan, Michele C. Hayward, Steven Bayer, Charles M. Perou, Philip S. Bernard, Prediction of lung cancer histological types by RT-qPCR gene expression in FFPE specimens, The Journal of Molecular Diagnostics, Volume 15, Issue 4, 2013, Pages 485\u2013497, ISSN 1525\u20131578, https:\/\/doi.org\/10.1016\/j.jmoldx.2013.03.007","journal-title":"The Journal of Molecular Diagnostics"},{"key":"337_CR4","doi-asserted-by":"crossref","unstructured":"A. Karlsson, H. Cirenajwis, K. Ericson-Lindqvist, C. Reutersw\u00e4rd, M. J\u00f6nsson, A. Patthey, A.F. Behndig, M. Johansson, M. Planck, J. Staaf, 19P Single sample predictor of non-small cell lung cancer histology based on gene expression analysis of archival tissue, Journal of Thoracic Oncology, Volume 13, Issue 4","DOI":"10.1016\/S1556-0864(18)30299-5"},{"issue":"3","key":"337_CR5","doi-asserted-by":"publisher","first-page":"720","DOI":"10.1183\/13993003.00035-2016","volume":"47","author":"WD Travis","year":"2016","unstructured":"Travis W.D., Brambilla E., Geisinger K.R., Histological grading in lung cancer: One system for all or separate systems for each histological type?, European Respiratory Journal, 2016, 47 (3), pp. 720\u2013723","journal-title":"European Respiratory Journal"},{"key":"337_CR6","doi-asserted-by":"publisher","first-page":"440","DOI":"10.1186\/s12885-019-5645-x","volume":"19","author":"S Visser","year":"2019","unstructured":"S. Visser, J. Hou, K. Bezemer, L. L. de Vogel, J. P. J. J. Hegmans, B. H. Stricker, S. Philipsen & J. G. J. V. Aerts. Prediction of response to pemetrexed in non-small-cell lung cancer with immunohistochemical phenotyping based on gene expression profiles. BMC Cancer 19, 440 (2019). https:\/\/doi.org\/10.1186\/s12885-019-5645-x","journal-title":"BMC Cancer"},{"issue":"4","key":"337_CR7","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0010312","volume":"5","author":"J Hou","year":"2010","unstructured":"Jun Hou, Joachim Aerts, Bianca den Hamer, Wilfred van IJcken, Michael den Bakker, Peter Riegman, Cor van der Leest, Peter van der Spek, John A. Foekens, Henk C. Hoogsteden, Frank Grosveld, and Sjaak Philipsen. (2010) Gene expression-based classification of non-small cell lung carcinomas and survival prediction. PLoS ONE 5(4): e10312. https:\/\/doi.org\/10.1371\/journal.pone.0010312","journal-title":"PLoS ONE"},{"issue":"13","key":"337_CR8","doi-asserted-by":"publisher","first-page":"E2970","DOI":"10.1073\/pnas.1717139115","volume":"115","author":"P Mobadersany","year":"2018","unstructured":"Pooya Mobadersany, Safoora Yousefi, Mohamed Amgad, David A. Gutman, Jill S. Barnholtz-Sloan, Jos\u00e9 E. Vel\u00e1zquez Vega, Daniel J. Brat, Lee A. D. Cooper, Predicting cancer outcomes from histology and genomics using convolutional networks, Proceedings of the National Academy of Sciences Mar 2018, 115 (13) E2970-E2979; DOI: https:\/\/doi.org\/10.1073\/pnas.1717139115","journal-title":"Proceedings of the National Academy of Sciences Mar"},{"key":"337_CR9","doi-asserted-by":"crossref","unstructured":"N. Zhang, J. Wu, M. Yang, J. Yu, R. Li, A composite model integrating imaging, histological, and genetic features to predict tumor mutation burden in non-small cell lung cancer patients, International Journal of Radiation Oncology Biology Physics, Volume 105, Issue 1, 2019","DOI":"10.1016\/j.ijrobp.2019.06.2460"},{"issue":"1","key":"337_CR10","doi-asserted-by":"publisher","first-page":"e13963","DOI":"10.1097\/MD.0000000000013963","volume":"98","author":"SR Digumarthy","year":"2019","unstructured":"Digumarthy SR, Padole AM, Gullo RL, Sequist LV, Kalra MK, Medicine (Baltimore), Can CT radiomic analysis in NSCLC predict histology and EGFR mutation status?, 2019;98(1):e13963. doi: https:\/\/doi.org\/10.1097\/MD.0000000000013963","journal-title":"Medicine (Baltimore)"},{"key":"337_CR11","doi-asserted-by":"publisher","first-page":"5207","DOI":"10.1038\/s41598-019-41585-4","volume":"9","author":"A Karlsson","year":"2019","unstructured":"Anna Karlsson, Helena Cirenajwis, Kajsa Ericson-Lindquist, Hans Brunnstr\u00f6m, Christel Reutersw\u00e4rd, Mats J\u00f6nsson, Cristian Ortiz-Villal\u00f3n, Aziz Hussein, Bengt Bergman, Anders Vikstr\u00f6m, Nastaran Monsef, Eva Branden, Hirsh Koyi, Luigi de Petris, Patrick Micke, Annika Patthey, Annelie F. Behndig, Mikael Johansson, Maria Planck & Johan Staaf. A combined gene expression tool for parallel histological prediction and gene fusion detection in non-small cell lung cancer. Scientific Reports 9, 5207 (2019) doi:https:\/\/doi.org\/10.1038\/s41598-019-41585-4","journal-title":"Scientific Reports"},{"key":"337_CR12","doi-asserted-by":"publisher","unstructured":"Tafadzwa Lawrence Chaunzwa, David C. Christiani, Michael Lanuti, Andrea Shafer, Nancy Diao, Raymond H. Mak, Hugo Aerts, Using deep-learning radiomics to predict lung cancer histology, Journal of Clinical Oncology 36, no. 15_suppl (2018), DOI: https:\/\/doi.org\/10.1200\/JCO.2018.36.15_suppl.8545","DOI":"10.1200\/JCO.2018.36.15_suppl.8545"},{"key":"337_CR13","doi-asserted-by":"publisher","unstructured":"Wu Weimiao, Parmar Chintan, Grossmann Patrick, Quackenbush John, Lambin Philippe, Bussink Johan, Mak Raymond, Aerts Hugo J. W. L., Exploratory study to identify radiomics classifiers for lung cancer histology, Frontiers in Oncology, Vol. 6, 2016, DOI=https:\/\/doi.org\/10.3389\/fonc.2016.00071","DOI":"10.3389\/fonc.2016.00071"},{"key":"337_CR14","doi-asserted-by":"publisher","first-page":"199","DOI":"10.1186\/s12931-018-0887-8","volume":"19","author":"B He","year":"2018","unstructured":"Bo He, Wei Zhao, Jiang-Yuan Pi, Dan Han, Yuan-Ming Jiang Zhen-Guang Zhang, Wei Zhao, A biomarker basing on radiomics for the prediction of overall survival in non\u2013small cell lung cancer patients, Respir Res (2018) 19: 199. https:\/\/doi.org\/10.1186\/s12931-018-0887-8","journal-title":"Respir Res"},{"key":"337_CR15","doi-asserted-by":"publisher","first-page":"1559","DOI":"10.1038\/s41591-018-0177-5","volume":"24","author":"N Coudray","year":"2018","unstructured":"Nicolas Coudray, Paolo Santiago Ocampo, Theodore Sakellaropoulos, Navneet Narula, Matija Snuderl, David Feny\u00f6, Andre L. Moreira, Narges Razavian & Aristotelis Tsirigos, Classification and mutation prediction from non\u2013small cell lung cancer histopathology images using deep learning. Nat Med 24, 1559\u20131567 (2018) doi:https:\/\/doi.org\/10.1038\/s41591-018-0177-5","journal-title":"Nat Med"},{"issue":"1","key":"337_CR16","doi-asserted-by":"publisher","first-page":"E194","DOI":"10.3390\/s19010194","volume":"19","author":"X Wang","year":"2019","unstructured":"Wang X, Mao K, Wang L, Yang P, Lu D, He P, Sensors (Basel), An appraisal of lung nodules automatic classification algorithms for CT images, 2019;19(1). E194. doi: https:\/\/doi.org\/10.3390\/s19010194","journal-title":"Sensors (Basel)"},{"issue":"Number 6","key":"337_CR17","doi-asserted-by":"publisher","first-page":"1045","DOI":"10.1007\/s10278-013-9622-7","volume":"26","author":"K Clark","year":"2013","unstructured":"Clark K, Vendt B, Smith K, Freymann J, Kirby J, Koppel P, Moore S, Phillips S, Maffitt D, Pringle M, Tarbox L, Prior F. The Cancer Imaging Archive (TCIA): maintaining and operating a public information repository, Journal of Digital Imaging, Volume 26, Number 6, 2013, pp 1045\u20131057","journal-title":"Journal of Digital Imaging"},{"key":"337_CR18","doi-asserted-by":"publisher","first-page":"387","DOI":"10.1148\/radiol.12111607","volume":"264","author":"O Gevaert","year":"2012","unstructured":"Olivier Gevaert, Jiajing Xu, Chuong D. Hoang, Ann N. Leung, Yue Xu, Andrew Quon, Daniel L. Rubin, Sandy Napel, Sylvia K. Plevritis (2012). Non\u2013small cell lung cancer: identifying prognostic imaging biomarkers by leveraging public gene expression microarray data\u2014methods and preliminary results. Radiology. Radiological Society of North America (RSNA). https:\/\/doi.org\/10.1148\/radiol.12111607, 264, 387, 396","journal-title":"Radiology. Radiological Society of North America (RSNA)."},{"key":"337_CR19","doi-asserted-by":"publisher","first-page":"24","DOI":"10.1007\/s13721-019-0204-6","volume":"8","author":"D Moitra","year":"2019","unstructured":"Moitra, D. & Mandal, R.K., Automated grading of non-small cell lung cancer by fuzzy rough nearest neighbour method, Netw Model Anal Health Inform Bioinforma (2019) 8: 24. https:\/\/doi.org\/10.1007\/s13721-019-0204-6","journal-title":"Netw Model Anal Health Inform Bioinforma"},{"key":"337_CR20","unstructured":"Zhiyong Cui, Ruimin Ke, Yinhai Wang. Deep bidirectional and unidirectional LSTM recurrent neural network for network-wide traffic speed prediction. arXiv:1801.02143"},{"key":"337_CR21","unstructured":"Xingjian Shi, Zhourong Chen, Hao Wang, Dit-Yan Yeung, Wai-kin Wong, Wang-chun Woo. Convolutional LSTM network: a machine learning approach for precipitation nowcasting. arXiv:1506.04214"},{"key":"337_CR22","unstructured":"Jeff Donahue, Lisa Anne Hendricks, Marcus Rohrbach, Subhashini Venugopalan, Sergio Guadarrama, Kate Saenko, Trevor Darrell. Long-term recurrent convolutional networks for visual recognition and description. arXiv:1411.4389"},{"key":"337_CR23","doi-asserted-by":"publisher","first-page":"14","DOI":"10.1007\/s13755-019-0077-1","volume":"7","author":"D Moitra","year":"2019","unstructured":"Moitra, D. & Mandal, R.K. Automated AJCC (7th edition) staging of non-small cell lung cancer (NSCLC) using deep convolutional neural network (CNN) and recurrent neural network (RNN). Health Inf Sci Syst (2019) 7: 14. https:\/\/doi.org\/10.1007\/s13755-019-0077-1","journal-title":"Health Inf Sci Syst"},{"key":"337_CR24","doi-asserted-by":"publisher","unstructured":"Bakr, Shaimaa; Gevaert, Olivier; Echegaray, Sebastian; Ayers, Kelsey; Zhou, Mu; Shafiq, Majid; Zheng, Hong; Zhang, Weiruo; Leung, Ann; Kadoch, Michael; Shrager, Joseph; Quon, Andrew; Rubin, Daniel; Plevritis, Sylvia; Napel, Sandy. (2017). Data for NSCLC Radiogenomics collection. The Cancer Imaging Archive. https:\/\/doi.org\/10.7937\/K9\/TCIA.2017.7hs46erv","DOI":"10.7937\/K9\/TCIA.2017.7hs46erv"},{"key":"337_CR25","unstructured":"D. Moitra, R. Mandal, Review of brain tumor detection using pattern recognition techniques, International Journal of Computer Sciences and Engineering, Vol. 5, Issue 2, pp. 121\u2013123, 2017"},{"key":"337_CR26","doi-asserted-by":"publisher","unstructured":"D. Moitra, Comparison of multimodal tumor image segmentation techniques, International Journal of Advanced Research in Computer Science, Volume 9, No. 3, 2018, https:\/\/doi.org\/10.26483\/ijarcs.v9i3.6010","DOI":"10.26483\/ijarcs.v9i3.6010"},{"key":"337_CR27","unstructured":"D. Moitra, R. Mandal, Segmentation strategy of PET brain tumor image, Indian Journal of Computer Science and Engineering, Vol. 8 No. 5 2017, e-ISSN:0976\u20135166"},{"key":"337_CR28","doi-asserted-by":"crossref","unstructured":"H. M. Nguyen, E. W. Cooper, K. Kamei, Borderline over-sampling for imbalanced data classification, International Journal of Knowledge Engineering and Soft Data Paradigms, 3(1), pp.4\u201321, 2009","DOI":"10.1504\/IJKESDP.2011.039875"},{"key":"337_CR29","unstructured":"Fran\u00e7ois Chollet, Deep learning with Python, Manning Publications Co., 2018, ISBN 9781617294433"},{"issue":"1","key":"337_CR30","first-page":"37","volume":"2","author":"DMW Powers","year":"2011","unstructured":"Powers, David M W (2011) [2007], Evaluation: from precision, recall and F-measure to ROC, informedness, markedness & correlation, Journal of Machine Learning Technologies. 2 (1): 37\u201363","journal-title":"Journal of Machine Learning Technologies."},{"issue":"8","key":"337_CR31","doi-asserted-by":"publisher","first-page":"1735","DOI":"10.1162\/neco.1997.9.8.1735","volume":"9","author":"S Hochreiter","year":"1997","unstructured":"Sepp Hochreiter and J\u00fcrgen Schmidhuber, Long short-term memory, Neural Computation, Volume 9 Issue 8, 1997, Pages 1735\u20131780, doi: https:\/\/doi.org\/10.1162\/neco.1997.9.8.1735","journal-title":"Neural Computation"},{"key":"337_CR32","unstructured":"Dipanjan Moitra, Classification of malignant tumors: a practical approach, LAP LAMBERT Academic Publishing, 2019, ISBN: 978-613-9-47500-1"},{"key":"337_CR33","unstructured":"Dipanjan Moitra, R. K. Samanta, Performance evaluation of BioPerl, Biojava, BioPython, BioRuby and BioSmalltalk for executing bioinformatics tasks, International Journal of Computer Sciences and Engineering, Vol.03, Issue.01, pp.157\u2013164, 2015"},{"key":"337_CR34","unstructured":"AJCC Cancer Stating Manual 7th Edition, American Joint Committee on Cancer, ISBN 978-0-387-88440-0, Springer New York"}],"container-title":["Journal of Digital Imaging"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10278-020-00337-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10278-020-00337-x\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10278-020-00337-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,4,25]],"date-time":"2021-04-25T06:08:05Z","timestamp":1619330885000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10278-020-00337-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,4,24]]},"references-count":34,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2020,8]]}},"alternative-id":["337"],"URL":"https:\/\/doi.org\/10.1007\/s10278-020-00337-x","relation":{},"ISSN":["0897-1889","1618-727X"],"issn-type":[{"value":"0897-1889","type":"print"},{"value":"1618-727X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,4,24]]},"assertion":[{"value":"24 April 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Compliance with Ethical Standards"}},{"value":"The authors declare that they have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of Interest"}},{"value":"For this type of study formal consent is not required.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical Approval"}},{"value":"Not applicable.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Informed Consent"}}]}}