{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,12]],"date-time":"2026-02-12T11:34:37Z","timestamp":1770896077436,"version":"3.50.1"},"reference-count":51,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2023,7,20]],"date-time":"2023-07-20T00:00:00Z","timestamp":1689811200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,7,20]],"date-time":"2023-07-20T00:00:00Z","timestamp":1689811200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100004775","name":"Natural Science Foundation of Gansu Province","doi-asserted-by":"crossref","award":["22JR1RA042"],"award-info":[{"award-number":["22JR1RA042"]}],"id":[{"id":"10.13039\/501100004775","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100004775","name":"Natural Science Foundation of Gansu Province","doi-asserted-by":"crossref","award":["22JR1RA042"],"award-info":[{"award-number":["22JR1RA042"]}],"id":[{"id":"10.13039\/501100004775","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100004775","name":"Natural Science Foundation of Gansu Province","doi-asserted-by":"crossref","award":["22JR1RA042"],"award-info":[{"award-number":["22JR1RA042"]}],"id":[{"id":"10.13039\/501100004775","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100004775","name":"Natural Science Foundation of Gansu Province","doi-asserted-by":"crossref","award":["22JR1RA042"],"award-info":[{"award-number":["22JR1RA042"]}],"id":[{"id":"10.13039\/501100004775","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Supercomput"],"published-print":{"date-parts":[[2024,1]]},"DOI":"10.1007\/s11227-023-05541-4","type":"journal-article","created":{"date-parts":[[2023,7,20]],"date-time":"2023-07-20T19:02:21Z","timestamp":1689879741000},"page":"1694-1727","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["A trustworthy neural architecture search framework for pneumonia image classification utilizing blockchain technology"],"prefix":"10.1007","volume":"80","author":[{"given":"Yi","family":"Yang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiaxuan","family":"Wei","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhixuan","family":"Yu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ruisheng","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,7,20]]},"reference":[{"key":"5541_CR1","doi-asserted-by":"publisher","unstructured":"He K, Zhang X, Ren S, Sun J (2016) Identity mappings in deep residual networks. In: European conference on computer vision 630\u2013645. https:\/\/doi.org\/10.1007\/978-3-319-46493-0_38","DOI":"10.1007\/978-3-319-46493-0_38"},{"key":"5541_CR2","doi-asserted-by":"publisher","unstructured":"Zhu Y, Newsam S (2017) Densenet for dense flow. In: 2017 IEEE International Conference on Image Processing (ICIP), pp 790\u2013794. https:\/\/doi.org\/10.1109\/ICIP.2017.8296389","DOI":"10.1109\/ICIP.2017.8296389"},{"key":"5541_CR3","unstructured":"Zoph B, Le Q (2017) Neural architecture search with reinforcement learning. In: International Conference on Learning Representations. https:\/\/openreview.net\/forum?id=r1Ue8Hcxg"},{"key":"5541_CR4","unstructured":"Real E, Moore S, Selle A, Saxena S, Suematsu YL, Tan J, Le QV, Kurakin A (2017) Large-scale evolution of image classifiers. In: Proceedings of the 34th International Conference on Machine Learning, pp 2902\u20132911. https:\/\/proceedings.mlr.press\/v70\/real17a.html"},{"key":"5541_CR5","unstructured":"Liu H, Simonyan K, Yang Y (2019) DARTS: Differentiable architecture search. In: International Conference on Learning Representations. https:\/\/openreview.net\/forum?id=S1eYHoC5FX"},{"key":"5541_CR6","doi-asserted-by":"publisher","unstructured":"Wright DCS (2008) Bitcoin: a peer-to-peer electronic cash system. Available at SSRN 3440802:21260. https:\/\/doi.org\/10.2139\/ssrn.3440802","DOI":"10.2139\/ssrn.3440802"},{"issue":"2\u20133","key":"5541_CR7","doi-asserted-by":"publisher","first-page":"90","DOI":"10.1016\/j.cviu.2006.08.002","volume":"104","author":"TB Moeslund","year":"2006","unstructured":"Moeslund TB, Hilton A, Kr\u00fcger V (2006) A survey of advances in vision-based human motion capture and analysis. Comput Vis Image Underst 104(2\u20133):90\u2013126. https:\/\/doi.org\/10.1016\/j.cviu.2006.08.002","journal-title":"Comput Vis Image Underst"},{"key":"5541_CR8","doi-asserted-by":"publisher","first-page":"398","DOI":"10.1016\/j.compeleceng.2019.04.017","volume":"76","author":"JJ Hathaliya","year":"2019","unstructured":"Hathaliya JJ, Tanwar S, Tyagi S, Kumar N (2019) Securing electronics healthcare records in healthcare 4.0: a biometric-based approach. Comput Electr Eng 76:398\u2013410. https:\/\/doi.org\/10.1016\/j.compeleceng.2019.04.017","journal-title":"Comput Electr Eng"},{"key":"5541_CR9","doi-asserted-by":"publisher","unstructured":"Szabo N (1997) Formalizing and securing relationships on public networks. First Monday 2(9). https:\/\/doi.org\/10.5210\/fm.v2i9.548","DOI":"10.5210\/fm.v2i9.548"},{"key":"5541_CR10","doi-asserted-by":"publisher","first-page":"102407","DOI":"10.1016\/j.jisa.2019.102407","volume":"50","author":"S Tanwar","year":"2020","unstructured":"Tanwar S, Parekh K, Evans R (2020) Blockchain-based electronic healthcare record system for healthcare 4.0 applications. J Inf Secur Appl 50:102407. https:\/\/doi.org\/10.1016\/j.jisa.2019.102407","journal-title":"J Inf Secur Appl"},{"key":"5541_CR11","doi-asserted-by":"publisher","DOI":"10.3390\/s22041448","author":"MA Almaiah","year":"2022","unstructured":"Almaiah MA, Hajjej F, Ali A, Pasha MF, Almomani O (2022) A novel hybrid trustworthy decentralized authentication and data preservation model for digital healthcare IoT based cps. Sensors. https:\/\/doi.org\/10.3390\/s22041448","journal-title":"Sensors"},{"key":"5541_CR12","doi-asserted-by":"publisher","DOI":"10.3390\/s22062112","author":"MA Almaiah","year":"2022","unstructured":"Almaiah MA, Ali A, Hajjej F, Pasha MF, Alohali MA (2022) A lightweight hybrid deep learning privacy preserving model for fc-based industrial internet of medical things. Sensors. https:\/\/doi.org\/10.3390\/s22062112","journal-title":"Sensors"},{"issue":"3","key":"5541_CR13","doi-asserted-by":"publisher","first-page":"183","DOI":"10.3390\/brainsci10030183","volume":"10","author":"A Pilozzi","year":"2020","unstructured":"Pilozzi A, Huang X (2020) Overcoming alzheimer\u2019s disease stigma by leveraging artificial intelligence and blockchain technologies. Brain Sci 10(3):183. https:\/\/doi.org\/10.3390\/brainsci10030183","journal-title":"Brain Sci"},{"key":"5541_CR14","doi-asserted-by":"publisher","first-page":"101812","DOI":"10.1016\/j.compmedimag.2020.101812","volume":"87","author":"R Kumar","year":"2021","unstructured":"Kumar R, Wang W, Kumar J, Yang T, Khan A, Ali W, Ali I (2021) An integration of blockchain and AI for secure data sharing and detection of CT images for the hospitals. Comput Med Imaging Graph 87:101812. https:\/\/doi.org\/10.1016\/j.compmedimag.2020.101812","journal-title":"Comput Med Imaging Graph"},{"issue":"1","key":"5541_CR15","doi-asserted-by":"publisher","first-page":"94","DOI":"10.3390\/electronics9010094","volume":"9","author":"A Khatoon","year":"2020","unstructured":"Khatoon A (2020) A blockchain-based smart contract system for healthcare management. Electronics 9(1):94. https:\/\/doi.org\/10.3390\/electronics9010094","journal-title":"Electronics"},{"issue":"1","key":"5541_CR16","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1038\/s41598-020-76550-z","volume":"10","author":"L Wang","year":"2020","unstructured":"Wang L, Lin ZQ, Wong A (2020) Covid-net: a tailored deep convolutional neural network design for detection of covid-19 cases from chest X-ray images. Sci Rep 10(1):1\u201312. https:\/\/doi.org\/10.1038\/s41598-020-76550-z","journal-title":"Sci Rep"},{"key":"5541_CR17","doi-asserted-by":"publisher","DOI":"10.32604\/cmc.2020.013232","author":"RA Al-Falluji","year":"2021","unstructured":"Al-Falluji RA, Katheeth ZD, Alathari B (2021) Automatic detection of covid-19 using chest X-ray images and modified resnet18-based convolution neural networks. Comput Mater Contin. https:\/\/doi.org\/10.32604\/cmc.2020.013232","journal-title":"Comput Mater Contin"},{"key":"5541_CR18","doi-asserted-by":"publisher","first-page":"116540","DOI":"10.1016\/j.eswa.2022.116540","volume":"195","author":"A Garg","year":"2022","unstructured":"Garg A, Salehi S, La Rocca M, Garner R, Duncan D (2022) Efficient and visualizable convolutional neural networks for Covid-19 classification using chest CT. Expert Syst Appl 195:116540. https:\/\/doi.org\/10.1016\/j.eswa.2022.116540","journal-title":"Expert Syst Appl"},{"key":"5541_CR19","doi-asserted-by":"publisher","first-page":"103792","DOI":"10.1016\/j.compbiomed.2020.103792","volume":"121","author":"T Ozturk","year":"2020","unstructured":"Ozturk T, Talo M, Yildirim EA, Baloglu UB, Yildirim O, Acharya UR (2020) Automated detection of covid-19 cases using deep neural networks with X-ray images. Comput Biol Med 121:103792. https:\/\/doi.org\/10.1016\/j.compbiomed.2020.103792","journal-title":"Comput Biol Med"},{"issue":"2","key":"5541_CR20","doi-asserted-by":"publisher","first-page":"854","DOI":"10.1007\/s10489-020-01829-7","volume":"51","author":"A Abbas","year":"2021","unstructured":"Abbas A, Abdelsamea MM, Gaber MM (2021) Classification of Covid-19 in chest x-ray images using detrac deep convolutional neural network. Appl Intell 51(2):854\u2013864. https:\/\/doi.org\/10.1007\/s10489-020-01829-7","journal-title":"Appl Intell"},{"issue":"1","key":"5541_CR21","doi-asserted-by":"publisher","first-page":"149","DOI":"10.1007\/s42600-021-00151-6","volume":"38","author":"E Luz","year":"2022","unstructured":"Luz E, Silva P, Silva R, Silva L, Guimar\u00e3es J, Miozzo G, Moreira G, Menotti D (2022) Towards an effective and efficient deep learning model for Covid-19 patterns detection in X-ray images. Res Biomed Eng 38(1):149\u2013162. https:\/\/doi.org\/10.1007\/s42600-021-00151-6","journal-title":"Res Biomed Eng"},{"key":"5541_CR22","doi-asserted-by":"publisher","first-page":"102583","DOI":"10.1016\/j.bspc.2021.102583","volume":"68","author":"FJP Montalbo","year":"2021","unstructured":"Montalbo FJP (2021) Diagnosing Covid-19 chest X-rays with a lightweight truncated densenet with partial layer freezing and feature fusion. Biomed Signal Process Control 68:102583. https:\/\/doi.org\/10.1016\/j.bspc.2021.102583","journal-title":"Biomed Signal Process Control"},{"key":"5541_CR23","doi-asserted-by":"publisher","DOI":"10.1145\/3065386","author":"A Krizhevsky","year":"2012","unstructured":"Krizhevsky A, Sutskever I, Hinton GE (2012) Imagenet classification with deep convolutional neural networks. Adv Neural Inf Process Syst. https:\/\/doi.org\/10.1145\/3065386","journal-title":"Adv Neural Inf Process Syst"},{"issue":"4","key":"5541_CR24","doi-asserted-by":"publisher","first-page":"100089","DOI":"10.1016\/j.bcra.2022.100089","volume":"3","author":"B Li","year":"2022","unstructured":"Li B, Lu Q, Jiang W, Jung T, Shi Y (2022) A collaboration strategy in the mining pool for proof-of-neural-architecture consensus. Blockchain Res Appl 3(4):100089. https:\/\/doi.org\/10.1016\/j.bcra.2022.100089","journal-title":"Blockchain Res Appl"},{"key":"5541_CR25","doi-asserted-by":"crossref","unstructured":"Zoph B, Vasudevan V, Shlens J, Le QV (2018) Learning transferable architectures for scalable image recognition. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)","DOI":"10.1109\/CVPR.2018.00907"},{"issue":"01","key":"5541_CR26","doi-asserted-by":"publisher","first-page":"4780","DOI":"10.1609\/aaai.v33i01.33014780","volume":"33","author":"E Real","year":"2019","unstructured":"Real E, Aggarwal A, Huang Y, Le QV (2019) Regularized evolution for image classifier architecture search. Proc AAAI Conf Artif Intell 33(01):4780\u20134789. https:\/\/doi.org\/10.1609\/aaai.v33i01.33014780","journal-title":"Proc AAAI Conf Artif Intell"},{"key":"5541_CR27","doi-asserted-by":"crossref","unstructured":"Chen X, Xie L, Wu J, Tian Q (2019) Progressive differentiable architecture search: Bridging the depth gap between search and evaluation. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision. Seoul, Korea, pp 1294\u20131303","DOI":"10.1109\/ICCV.2019.00138"},{"key":"5541_CR28","doi-asserted-by":"crossref","unstructured":"Xie L, Yuille A (2017) Genetic cnn. In: Proceedings of the IEEE International Conference on Computer Vision. Venice, Italy, pp 1379\u20131388","DOI":"10.1109\/ICCV.2017.154"},{"key":"5541_CR29","doi-asserted-by":"publisher","first-page":"109193","DOI":"10.1016\/j.patcog.2022.109193","volume":"136","author":"W Wang","year":"2023","unstructured":"Wang W, Zhang X, Cui H, Yin H, Zhang Y (2023) Fp-darts: fast parallel differentiable neural architecture search for image classification. Pattern Recogn 136:109193. https:\/\/doi.org\/10.1016\/j.patcog.2022.109193","journal-title":"Pattern Recogn"},{"key":"5541_CR30","doi-asserted-by":"publisher","DOI":"10.1016\/j.compmedimag.2023.102268","author":"S Qin","year":"2023","unstructured":"Qin S, Zhang Z, Jiang Y, Cui S, Cheng S, Li Z (2023) Ng-nas: node growth neural architecture search for 3d medical image segmentation. Comput Med Imag Graph. https:\/\/doi.org\/10.1016\/j.compmedimag.2023.102268","journal-title":"Comput Med Imag Graph"},{"key":"5541_CR31","doi-asserted-by":"publisher","first-page":"45","DOI":"10.1016\/j.jnca.2018.10.020","volume":"126","author":"Q Feng","year":"2019","unstructured":"Feng Q, He D, Zeadally S, Khan MK, Kumar N (2019) A survey on privacy protection in blockchain system. J Netw Comput Appl 126:45\u201358. https:\/\/doi.org\/10.1016\/j.jnca.2018.10.020","journal-title":"J Netw Comput Appl"},{"key":"5541_CR32","doi-asserted-by":"publisher","first-page":"2440","DOI":"10.1109\/TIFS.2020.2969565","volume":"15","author":"C Lin","year":"2020","unstructured":"Lin C, He D, Huang X, Khan MK, Choo K-KR (2020) Dcap: a secure and efficient decentralized conditional anonymous payment system based on blockchain. IEEE Trans Inf Forensics Secur 15:2440\u20132452. https:\/\/doi.org\/10.1109\/TIFS.2020.2969565","journal-title":"IEEE Trans Inf Forensics Secur"},{"key":"5541_CR33","doi-asserted-by":"publisher","first-page":"33","DOI":"10.1016\/j.cca.2020.04.016","volume":"508","author":"G-Z Zhang","year":"2020","unstructured":"Zhang G-Z, Deng Y-J, Xie Q-Q, Ren E-H, Ma Z-J, He X-G, Gao Y-C, Kang X-W (2020) Sirtuins and intervertebral disc degeneration: roles in inflammation, oxidative stress, and mitochondrial function. Clin Chim Acta 508:33\u201342. https:\/\/doi.org\/10.1016\/j.cca.2020.04.016","journal-title":"Clin Chim Acta"},{"key":"5541_CR34","doi-asserted-by":"publisher","first-page":"2292","DOI":"10.1109\/ACCESS.2016.2566339","volume":"4","author":"K Christidis","year":"2016","unstructured":"Christidis K, Devetsikiotis M (2016) Blockchains and smart contracts for the internet of things. Ieee Access 4:2292\u20132303. https:\/\/doi.org\/10.1109\/ACCESS.2016.2566339","journal-title":"Ieee Access"},{"key":"5541_CR35","doi-asserted-by":"publisher","unstructured":"Dinh TTA, Wang J, Chen G, Liu R, Ooi BC, Tan K-L (2017) Blockbench: a framework for analyzing private blockchains. In: Proceedings of the 2017 ACM International Conference on Management of Data, pp 1085\u20131100. https:\/\/doi.org\/10.1145\/3035918.3064033","DOI":"10.1145\/3035918.3064033"},{"key":"5541_CR36","unstructured":"Linn LA, Koo MB, et al (2016) Blockchain for health data and its potential use in health it and health care related research. ONC\/NIST Use of Blockchain for Healthcare and Research Workshop. Gaithersburg, Maryland, United States: ONC\/NIST 1\u201310"},{"key":"5541_CR37","doi-asserted-by":"publisher","unstructured":"Azaria A, Ekblaw A, Vieira T, Lippman A (2016) Medrec: using blockchain for medical data access and permission management. In: 2016 2nd International Conference on Open and Big Data (OBD). IEEE, pp 25\u201330. https:\/\/doi.org\/10.1109\/OBD.2016.11","DOI":"10.1109\/OBD.2016.11"},{"key":"5541_CR38","doi-asserted-by":"publisher","DOI":"10.4018\/978-1-7998-3632-2.ch003","author":"A Ozsoy","year":"2020","unstructured":"Ozsoy A, Gezici B, B\u00f6l\u00fcc\u00fc N, B\u00f6l\u00fcc\u00fc N (2020) Blockchain technology applications in government. Cross-Ind Use Blockchain Technol Oppor Future. https:\/\/doi.org\/10.4018\/978-1-7998-3632-2.ch003","journal-title":"Cross-Ind Use Blockchain Technol Oppor Future"},{"key":"5541_CR39","doi-asserted-by":"publisher","unstructured":"Muralidharan S, Ko H (2019) An interplanetary file system (ipfs) based IoT framework. In: 2019 IEEE International Conference on Consumer Electronics (ICCE). IEEE, pp 1\u20132. https:\/\/doi.org\/10.1109\/ICCE.2019.8662002","DOI":"10.1109\/ICCE.2019.8662002"},{"key":"5541_CR40","doi-asserted-by":"publisher","unstructured":"Zhu L, Dong H, Shen M, Gai K (2019) An incentive mechanism using shapley value for blockchain-based medical data sharing. In: 2019 IEEE 5th Intl Conference on Big Data Security on Cloud (BigDataSecurity), IEEE Intl Conference on High Performance and Smart Computing, (HPSC) and IEEE Intl Conference on Intelligent Data and Security (IDS), pp 113\u2013118. https:\/\/doi.org\/10.1109\/BigDataSecurity-HPSC-IDS.2019.00030","DOI":"10.1109\/BigDataSecurity-HPSC-IDS.2019.00030"},{"key":"5541_CR41","doi-asserted-by":"publisher","unstructured":"Liu J, Li X, Ye L, Zhang H, Du X, Guizani M (2018) Bpds: a blockchain based privacy-preserving data sharing for electronic medical records. In: 2018 IEEE Global Communications Conference (GLOBECOM). IEEE, pp 1\u20136. https:\/\/doi.org\/10.1109\/GLOCOM.2018.8647713","DOI":"10.1109\/GLOCOM.2018.8647713"},{"key":"5541_CR42","doi-asserted-by":"publisher","unstructured":"Eltayieb N, Sun L, Wang K, Li F (2019) A certificateless proxy re-encryption scheme for cloud-based blockchain. In: International Conference on Frontiers in Cyber Security. Springer, pp 293\u2013307. https:\/\/doi.org\/10.1007\/978-981-15-0818-9_19","DOI":"10.1007\/978-981-15-0818-9_19"},{"key":"5541_CR43","doi-asserted-by":"publisher","first-page":"136481","DOI":"10.1109\/ACCESS.2019.2940052","volume":"7","author":"H Kim","year":"2019","unstructured":"Kim H, Kim S-H, Hwang JY, Seo C (2019) Efficient privacy-preserving machine learning for blockchain network. Ieee Access 7:136481\u2013136495. https:\/\/doi.org\/10.1109\/ACCESS.2019.2940052","journal-title":"Ieee Access"},{"issue":"2","key":"5541_CR44","doi-asserted-by":"publisher","first-page":"197","DOI":"10.1109\/MNET.001.1900310","volume":"27","author":"Y Fu","year":"2020","unstructured":"Fu Y, Yu FR, Li C, Luan TH, Zhang Y (2020) Vehicular blockchain-based collective learning for connected and autonomous vehicles. IEEE Wirel Commun 27(2):197\u2013203. https:\/\/doi.org\/10.1109\/MNET.001.1900310","journal-title":"IEEE Wirel Commun"},{"issue":"9","key":"5541_CR45","doi-asserted-by":"publisher","first-page":"13855","DOI":"10.1007\/s11042-022-13843-7","volume":"82","author":"H Malik","year":"2023","unstructured":"Malik H, Anees T, Din M, Naeem A (2023) Cdc_net: multi-classification convolutional neural network model for detection of Covid-19, pneumothorax, pneumonia, lung cancer, and tuberculosis using chest x-rays. Multimed Tools Appl 82(9):13855\u201313880. https:\/\/doi.org\/10.1007\/s11042-022-13843-7","journal-title":"Multimed Tools Appl"},{"issue":"1","key":"5541_CR46","doi-asserted-by":"publisher","first-page":"015036","DOI":"10.1088\/2632-2153\/acc30f","volume":"4","author":"KM Abubeker","year":"2023","unstructured":"Abubeker KM, Baskar S (2023) B2-net: an artificial intelligence powered machine learning framework for the classification of pneumonia in chest X-ray images. Mach Learn Sci Technol 4(1):015036. https:\/\/doi.org\/10.1088\/2632-2153\/acc30f","journal-title":"Mach Learn Sci Technol"},{"key":"5541_CR47","doi-asserted-by":"publisher","first-page":"1","DOI":"10.17632\/9xkhgts2s6.1","volume":"1","author":"U Sait","year":"2020","unstructured":"Sait U, Lal K, Prajapati S, Bhaumik R, Kumar T, Sanjana S, Bhalla K (2020) Curated dataset for covid-19 posterior-anterior chest radiography images (X-rays). Mendeley Data 1:1. https:\/\/doi.org\/10.17632\/9xkhgts2s6.1","journal-title":"Mendeley Data"},{"key":"5541_CR48","unstructured":"Krizhevsky A, Hinton G, et al (2009) Learning multiple layers of features from tiny images"},{"key":"5541_CR49","doi-asserted-by":"publisher","first-page":"132665","DOI":"10.1109\/ACCESS.2020.3010287","volume":"8","author":"MEH Chowdhury","year":"2020","unstructured":"Chowdhury MEH, Rahman T, Khandakar A, Mazhar R, Kadir MA, Mahbub ZB, Islam KR, Khan MS, Iqbal A, Emadi NA, Reaz MBI, Islam MT (2020) Can AI help in screening viral and Covid-19 pneumonia? IEEE Access 8:132665\u2013132676. https:\/\/doi.org\/10.1109\/ACCESS.2020.3010287","journal-title":"IEEE Access"},{"key":"5541_CR50","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2021.104319","volume":"132","author":"T Rahman","year":"2021","unstructured":"Rahman T, Khandakar A, Qiblawey Y, Tahir A, Kiranyaz S, Abul Kashem SB, Islam MT, Al Maadeed S, Zughaier SM, Khan MS, Chowdhury MEH (2021) Exploring the effect of image enhancement techniques on Covid-19 detection using chest X-ray images. Comput Biol Med 132:104319. https:\/\/doi.org\/10.1016\/j.compbiomed.2021.104319","journal-title":"Comput Biol Med"},{"key":"5541_CR51","unstructured":"Borkowski AA, Bui MM, Thomas LB, Wilson CP, DeLand LA, Mastorides SM (2019) Lung and colon cancer histopathological image dataset (lc25000). arXiv preprint arXiv:1912.12142"}],"updated-by":[{"DOI":"10.1007\/s11227-023-05760-9","type":"correction","label":"Correction","source":"publisher","updated":{"date-parts":[[2023,11,10]],"date-time":"2023-11-10T00:00:00Z","timestamp":1699574400000}}],"container-title":["The Journal of Supercomputing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11227-023-05541-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11227-023-05541-4\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11227-023-05541-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,15]],"date-time":"2024-01-15T09:23:06Z","timestamp":1705310586000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11227-023-05541-4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,7,20]]},"references-count":51,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2024,1]]}},"alternative-id":["5541"],"URL":"https:\/\/doi.org\/10.1007\/s11227-023-05541-4","relation":{"correction":[{"id-type":"doi","id":"10.1007\/s11227-023-05760-9","asserted-by":"object"}]},"ISSN":["0920-8542","1573-0484"],"issn-type":[{"value":"0920-8542","type":"print"},{"value":"1573-0484","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,7,20]]},"assertion":[{"value":"5 July 2023","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"20 July 2023","order":2,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"10 November 2023","order":3,"name":"change_date","label":"Change Date","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"Correction","order":4,"name":"change_type","label":"Change Type","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"A Correction to this paper has been published:","order":5,"name":"change_details","label":"Change Details","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"https:\/\/doi.org\/10.1007\/s11227-023-05760-9","URL":"https:\/\/doi.org\/10.1007\/s11227-023-05760-9","order":6,"name":"change_details","label":"Change Details","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"}},{"value":"All authors consent to publication.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent to publish"}},{"value":"This work does not involve any work related to ethics.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval"}}]}}