{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T17:13:31Z","timestamp":1740158011890,"version":"3.37.3"},"reference-count":22,"publisher":"Springer Science and Business Media LLC","issue":"10","license":[{"start":{"date-parts":[[2022,6,21]],"date-time":"2022-06-21T00:00:00Z","timestamp":1655769600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2022,6,21]],"date-time":"2022-06-21T00:00:00Z","timestamp":1655769600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"name":"Project for Research on Medical in Jiangsu Commission of Health","award":["Z2020032"],"award-info":[{"award-number":["Z2020032"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["No.62102345"],"award-info":[{"award-number":["No.62102345"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"The Youth Medical Science and Technology Innovation Project of Xuzhou Municipal Health Commission","award":["XWKYHT20210586"],"award-info":[{"award-number":["XWKYHT20210586"]}]},{"name":"Special support for Young Talents of the Affiliated Hospital of Xuzhou Medical University","award":["2020QQMRC08"],"award-info":[{"award-number":["2020QQMRC08"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Ambient Intell Human Comput"],"published-print":{"date-parts":[[2023,10]]},"DOI":"10.1007\/s12652-022-04026-1","type":"journal-article","created":{"date-parts":[[2022,6,21]],"date-time":"2022-06-21T19:39:42Z","timestamp":1655840382000},"page":"13729-13740","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Intelligent diagnosis of bladder cancer with limited MRI data"],"prefix":"10.1007","volume":"14","author":[{"given":"Xiuqing","family":"Chen","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qianqian","family":"Xu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Huachang","family":"Xu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiawei","family":"Wu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Enze","family":"Zhu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1676-940X","authenticated-orcid":false,"given":"Hong","family":"Zhu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,6,21]]},"reference":[{"key":"4026_CR1","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1038\/ncomms5644","volume":"5","author":"H Aerts","year":"2014","unstructured":"Aerts H, Velazquez ER, Leijenaar R et al (2014) Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach. Nat Commun 5:1\u20138. https:\/\/doi.org\/10.1038\/ncomms5644","journal-title":"Nat Commun"},{"key":"4026_CR2","unstructured":"AJCC Cancer Staging System (2020) http:\/\/www.cancerstaging.org\/references-tools\/Pages\/What-is-Cancer-Staging.aspx. Accessed 28 June 2020"},{"issue":"5","key":"4026_CR3","doi-asserted-by":"publisher","first-page":"1207","DOI":"10.1109\/TMI.2016.2535865","volume":"35","author":"M Anthimopoulos","year":"2016","unstructured":"Anthimopoulos M, Christodoulidis S, Ebner L, Christe A, Mougiakakou S (2016) Lung pattern classification for interstitial lung diseases using a deep convolutional neural network. IEEE Trans Med Imaging 35(5):1207\u20131216. https:\/\/doi.org\/10.1109\/TMI.2016.2535865","journal-title":"IEEE Trans Med Imaging"},{"issue":"7","key":"4026_CR4","doi-asserted-by":"publisher","first-page":"962","DOI":"10.1016\/j.ophtha.2017.02.008","volume":"124","author":"R Gargeya","year":"2017","unstructured":"Gargeya R, Leng T (2017) Automated identification of diabetic retinopathy using deep learning. Ophthalmology 124(7):962\u2013969. https:\/\/doi.org\/10.1016\/j.ophtha.2017.02.008","journal-title":"Ophthalmology"},{"key":"4026_CR5","doi-asserted-by":"publisher","unstructured":"He KM, Zhang XY, Ren SQ, Sun J (2016) Deep residual learning for image recognition. In: 2016 IEEE conference on computer vision and pattern recognition (CVPR), pp 770\u2013778. https:\/\/doi.org\/10.1109\/CVPR.2016.90","DOI":"10.1109\/CVPR.2016.90"},{"key":"4026_CR6","doi-asserted-by":"publisher","unstructured":"Jazvi\u0107 M, Ru\u017ei\u0107 B, Kru\u0161lin B et al (2019) Clinical recommendations for diagnosis, treatment and monitoring of patients with bladder cancer. Lijec\u0306nic\u0306ki Vjesnik. https:\/\/doi.org\/10.26800\/LV-141-11-12-42","DOI":"10.26800\/LV-141-11-12-42"},{"issue":"8","key":"4026_CR7","doi-asserted-by":"publisher","first-page":"3631","DOI":"10.1007\/s00500-022-06822-5","volume":"26","author":"DH Jiang","year":"2022","unstructured":"Jiang DH, Zhang S, Dai L, Dai YM (2022) Multi-scale generative adversarial network for image super-resolution. Soft Comput 26(8):3631\u20133641. https:\/\/doi.org\/10.1007\/s00500-022-06822-5","journal-title":"Soft Comput"},{"issue":"19","key":"4026_CR8","doi-asserted-by":"publisher","first-page":"1980","DOI":"10.1001\/jama.2020.17598","volume":"324","author":"AT Lenis","year":"2020","unstructured":"Lenis AT, Lec PM, Chamie K, Mshs MD (2020) Bladder cancer: a review. JAMA 324(19):1980\u20131991. https:\/\/doi.org\/10.1001\/jama.2020.17598","journal-title":"JAMA"},{"issue":"52","key":"4026_CR9","doi-asserted-by":"publisher","DOI":"10.1097\/MD.0000000000023645","volume":"99","author":"D Lin","year":"2020","unstructured":"Lin D, Yu Q, Lu Y, Cao L, Hu TH, He PL, Yang J, Wang YL, Cui S, Wu T (2020) Bayesian network analysis of open, laparoscopic, and robot-assisted radical cystectomy for bladder cancer. Medicine 99(52):e23645. https:\/\/doi.org\/10.1097\/MD.0000000000023645","journal-title":"Medicine"},{"key":"4026_CR10","doi-asserted-by":"publisher","first-page":"3264801","DOI":"10.1155\/2020\/3264801","volume":"2020","author":"Z Liu","year":"2020","unstructured":"Liu Z, Zhang GR, Zhao JY, Yu LY, Sheng JX, Zhang N, Yuan H (2020) Second-generation sequencing with deep reinforcement learning for lung infection detection. J Healthc Eng 2020:3264801. https:\/\/doi.org\/10.1155\/2020\/3264801","journal-title":"J Healthc Eng"},{"issue":"5","key":"4026_CR11","doi-asserted-by":"publisher","first-page":"404","DOI":"10.3322\/caac.21631","volume":"70","author":"VG Patel","year":"2020","unstructured":"Patel VG, Oh WK, Galsky MD (2020) Treatment of muscle-invasive and advanced bladder cancer in 2020. CA Cancer J Clin 70(5):404\u2013423. https:\/\/doi.org\/10.3322\/caac.21631","journal-title":"CA Cancer J Clin"},{"key":"4026_CR12","doi-asserted-by":"publisher","unstructured":"Sarraf S, Tofighi G (2016) Classification of Alzheimer's disease structural MRI data by deep learning convolutional neural networks. ArXiv: abs\/1607.06583. https:\/\/doi.org\/10.48550\/arXiv.1607.06583","DOI":"10.48550\/arXiv.1607.06583"},{"issue":"11","key":"4026_CR13","doi-asserted-by":"publisher","first-page":"2298","DOI":"10.1109\/TPAMI.2016.2646371","volume":"39","author":"BG Shi","year":"2017","unstructured":"Shi BG, Bai X, Yao C (2017) An end-to-end trainable neural network for image-based sequence recognition and its application to scene text recognition. IEEE Trans Pattern Anal Mach Intell 39(11):2298\u20132340. https:\/\/doi.org\/10.1109\/TPAMI.2016.2646371","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"6","key":"4026_CR14","doi-asserted-by":"publisher","first-page":"2920","DOI":"10.21037\/tau.2020.02.10","volume":"9","author":"C Tholomier","year":"2020","unstructured":"Tholomier C, Souhami L, Kassouf W (2020) Bladder-sparing protocols in the treatment of muscle-invasive bladder cancer. Transl Androl Urol 9(6):2920\u20132937. https:\/\/doi.org\/10.21037\/tau.2020.02.10","journal-title":"Transl Androl Urol"},{"issue":"24","key":"4026_CR15","doi-asserted-by":"publisher","first-page":"16284","DOI":"10.1021\/acs.analchem.0c04282","volume":"92","author":"Z Wang","year":"2020","unstructured":"Wang Z, Chen J, Yang L et al (2020) Single-cell sequencing-enabled hexokinase 2 assay for noninvasive bladder cancer diagnosis and screening by detecting rare malignant cells in urine. Anal Chem 92(24):16284\u201316292. https:\/\/doi.org\/10.1021\/acs.analchem.0c04282","journal-title":"Anal Chem"},{"issue":"1","key":"4026_CR16","doi-asserted-by":"publisher","first-page":"82","DOI":"10.1016\/j.eururo.2020.03.055","volume":"79","author":"JA Witjes","year":"2021","unstructured":"Witjes JA, Bruins HM, Cathomas R et al (2021) European Association of Urology guidelines on muscle-invasive and metastatic bladder cancer: summary of the 2020 guidelines. Eur Urol 79(1):82\u2013104. https:\/\/doi.org\/10.1016\/j.eururo.2020.03.055","journal-title":"Eur Urol"},{"key":"4026_CR17","doi-asserted-by":"publisher","unstructured":"Woo S, Park J, Lee J, Kweon IS (2018) CBAM: convolutional block attention module. Springer, Cham, pp 3\u201319. https:\/\/doi.org\/10.1007\/978-3-030-01234-2_1","DOI":"10.1007\/978-3-030-01234-2_1"},{"key":"4026_CR18","doi-asserted-by":"publisher","DOI":"10.3389\/fimmu.2020.590618","volume":"11","author":"XK Wu","year":"2020","unstructured":"Wu XK, Lv DJ, Cai C, Zhao ZJ, Wang M, Chen WZ, Liu YD (2020) A TP53-associated immune prognostic signature for the prediction of overall survival and therapeutic responses in muscle-invasive bladder cancer. Front Immunol 11:590618. https:\/\/doi.org\/10.3389\/fimmu.2020.590618","journal-title":"Front Immunol"},{"issue":"2","key":"4026_CR19","doi-asserted-by":"publisher","first-page":"244","DOI":"10.3390\/diagnostics11020244","volume":"11","author":"K Yoneda","year":"2021","unstructured":"Yoneda K, Kamiya N, Utsumi T, Wakai K, Oka R, Endo T, Yano M, Hiruta N, Ichikawa T, Suzuki H (2021) Impact of lymphovascular invasion on prognosis in the patients with bladder cancer-comparison of transurethral resection and radical cystectomy. Diagnostics (basel, Switzerland) 11(2):244. https:\/\/doi.org\/10.3390\/diagnostics11020244","journal-title":"Diagnostics (basel, Switzerland)"},{"key":"4026_CR20","doi-asserted-by":"publisher","first-page":"1","DOI":"10.48550\/arXiv.1411.1792","volume":"27","author":"J Yosinski","year":"2014","unstructured":"Yosinski J, Clune J, Bengio Y, Lipson H (2014) How transferable are features in deep neural networks? Adv Neural Inf Process Syst 27:1. https:\/\/doi.org\/10.48550\/arXiv.1411.1792","journal-title":"Adv Neural Inf Process Syst"},{"issue":"12","key":"4026_CR21","doi-asserted-by":"publisher","first-page":"2707","DOI":"10.1007\/s00345-019-02734-6","volume":"37","author":"S Zamboni","year":"2019","unstructured":"Zamboni S, Moschini M, Gallina A et al (2019) The impact of completeness of last transurethral resection of bladder tumors on the outcomes of radical cystectomy. World J Urol 37(12):2707\u20132714. https:\/\/doi.org\/10.1007\/s00345-019-02734-6","journal-title":"World J Urol"},{"issue":"15","key":"4026_CR22","doi-asserted-by":"publisher","first-page":"4259","DOI":"10.1158\/1078-0432.CCR-16-2910","volume":"23","author":"B Zhang","year":"2017","unstructured":"Zhang B, Tian J, Dong D et al (2017) Radiomics features of multiparametric MRI as novel prognostic factors in advanced nasopharyngeal carcinoma. Clin Cancer Res 23(15):4259\u20134269. https:\/\/doi.org\/10.1158\/1078-0432.CCR-16-2910","journal-title":"Clin Cancer Res"}],"container-title":["Journal of Ambient Intelligence and Humanized Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12652-022-04026-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s12652-022-04026-1\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12652-022-04026-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,8,22]],"date-time":"2023-08-22T18:38:49Z","timestamp":1692729529000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s12652-022-04026-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,6,21]]},"references-count":22,"journal-issue":{"issue":"10","published-print":{"date-parts":[[2023,10]]}},"alternative-id":["4026"],"URL":"https:\/\/doi.org\/10.1007\/s12652-022-04026-1","relation":{},"ISSN":["1868-5137","1868-5145"],"issn-type":[{"type":"print","value":"1868-5137"},{"type":"electronic","value":"1868-5145"}],"subject":[],"published":{"date-parts":[[2022,6,21]]},"assertion":[{"value":"12 November 2020","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"30 May 2022","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"21 June 2022","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare that they have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}