{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,23]],"date-time":"2026-01-23T16:47:22Z","timestamp":1769186842951,"version":"3.49.0"},"reference-count":38,"publisher":"Springer Science and Business Media LLC","issue":"17","license":[{"start":{"date-parts":[[2017,7,18]],"date-time":"2017-07-18T00:00:00Z","timestamp":1500336000000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100001809","name":"NSFC","doi-asserted-by":"crossref","award":["61602250"],"award-info":[{"award-number":["61602250"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100004608","name":"Natural Science Foundation of Jiangsu Province","doi-asserted-by":"publisher","award":["BK20150983"],"award-info":[{"award-number":["BK20150983"]}],"id":[{"id":"10.13039\/501100004608","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Multimed Tools Appl"],"published-print":{"date-parts":[[2018,9]]},"DOI":"10.1007\/s11042-017-5023-0","type":"journal-article","created":{"date-parts":[[2017,7,18]],"date-time":"2017-07-18T02:09:44Z","timestamp":1500343784000},"page":"22629-22648","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":75,"title":["Smart pathological brain detection by synthetic minority oversampling technique, extreme learning machine, and Jaya algorithm"],"prefix":"10.1007","volume":"77","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4870-1493","authenticated-orcid":false,"given":"Yu-Dong","family":"Zhang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guihu","family":"Zhao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Junding","family":"Sun","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaosheng","family":"Wu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhi-Heng","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hong-Min","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Vishnu Varthanan","family":"Govindaraj","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tianmin","family":"Zhan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jianwu","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2017,7,18]]},"reference":[{"key":"5023_CR1","doi-asserted-by":"publisher","unstructured":"Chen Y (2016) Voxelwise detection of cerebral microbleed in CADASIL patients by leaky rectified linear unit and early stopping: A class-imbalanced susceptibility-weighted imaging data study. Multimed Tools Appl. doi: 10.1007\/s11042-017-4383-9 (Online)","DOI":"10.1007\/s11042-017-4383-9"},{"key":"5023_CR2","doi-asserted-by":"crossref","first-page":"5937","DOI":"10.1109\/ACCESS.2016.2611530","volume":"4","author":"X-Q Chen","year":"2016","unstructured":"Chen X-Q (2016) Fractal dimension estimation for developing pathological brain detection system based on Minkowski-Bouligand method. IEEE Access 4:5937\u20135947","journal-title":"IEEE Access"},{"key":"5023_CR3","doi-asserted-by":"publisher","unstructured":"Chen H (2017) Seven-layer deep neural network based on sparse autoencoder for voxelwise detection of cerebral microbleed. Multimed Tools Appl. doi: 10.1007\/s11042-017-4554-8 (Online)","DOI":"10.1007\/s11042-017-4554-8"},{"issue":"1\u20134","key":"5023_CR4","first-page":"275","volume":"151","author":"P Chen","year":"2017","unstructured":"Chen P, Du S (2017) Pathological Brain Detection via Wavelet Packet Tsallis Entropy and Real-Coded Biogeography-based Optimization. Fundamenta Informaticae 151(1\u20134):275\u2013291","journal-title":"Fundamenta Informaticae"},{"key":"5023_CR5","doi-asserted-by":"crossref","first-page":"345","DOI":"10.1016\/j.neucom.2016.12.029","volume":"230","author":"K Chen","year":"2017","unstructured":"Chen K, Lv Q, Lu Y et al (2017) Robust regularized extreme learning machine for regression using iteratively reweighted least squares. Neurocomputing 230:345\u2013358","journal-title":"Neurocomputing"},{"key":"5023_CR6","doi-asserted-by":"crossref","first-page":"1","DOI":"10.2528\/PIER13010105","volume":"137","author":"S Das","year":"2013","unstructured":"Das S, Chowdhury M, Kundu MK (2013) Brain MR image classification using multiscale geometric analysis of Ripplet. Progress in Electromagnetics Research-Pier 137:1\u201317","journal-title":"Progress in Electromagnetics Research-Pier"},{"key":"5023_CR7","doi-asserted-by":"crossref","unstructured":"Doreswamy, Salma MU (2015) BAT-ELM: a bio inspired model for prediction of breast cancer data. In: International Conference on Applied and Theoretical Computing And Communication Technology (Icatcct). Davangere, IEEE, pp. 501\u2013506","DOI":"10.1109\/ICATCCT.2015.7456936"},{"issue":"7641","key":"5023_CR8","doi-asserted-by":"crossref","first-page":"348","DOI":"10.1038\/nature21369","volume":"542","author":"HC Hazlett","year":"2017","unstructured":"Hazlett HC, Gu HB, Munsell BC et al (2017) Early brain development in infants at high risk for autism spectrum disorder. Nature 542(7641):348","journal-title":"Nature"},{"key":"5023_CR9","doi-asserted-by":"crossref","first-page":"197","DOI":"10.1016\/j.neuroimage.2016.05.030","volume":"138","author":"Y Huo","year":"2016","unstructured":"Huo Y, Plassard AJ, Carass A et al (2016) Consistent cortical reconstruction and multi-atlas brain segmentation. NeuroImage 138:197\u2013210","journal-title":"NeuroImage"},{"key":"5023_CR10","doi-asserted-by":"crossref","unstructured":"Huo Y, Carass A, Resnick SM et al (2016) Combining Multi-atlas Segmentation with Brain Surface Estimation. In: Conference on Medical Imaging - Image Processing. San Diego, Spie-Int Soc Optical Engineering, p 97840E","DOI":"10.1117\/12.2216604"},{"issue":"2","key":"5023_CR11","doi-asserted-by":"crossref","first-page":"599","DOI":"10.1002\/hbm.23432","volume":"38","author":"YK Huo","year":"2017","unstructured":"Huo YK, Asman AJ, Plassard AJ et al (2017) Simultaneous total intracranial volume and posterior fossa volume estimation using multi-atlas label fusion. Hum Brain Mapp 38(2):599\u2013616","journal-title":"Hum Brain Mapp"},{"key":"5023_CR12","doi-asserted-by":"publisher","unstructured":"Jiang Y, Zhu W (2017) Exploring a smart pathological brain detection method on pseudo Zernike moment. Multimed Tools Appl. doi: 10.1007\/s11042-017-4703-0 (Online)","DOI":"10.1007\/s11042-017-4703-0"},{"issue":"1","key":"5023_CR13","doi-asserted-by":"crossref","first-page":"117","DOI":"10.1007\/s00778-014-0366-x","volume":"24","author":"H Li","year":"2015","unstructured":"Li H, Bhowmick SS, Sun AX et al (2015) Conformity-aware influence maximization in online social networks. VLDB J 24(1):117\u2013141","journal-title":"VLDB J"},{"issue":"1","key":"5023_CR14","volume":"4","author":"G Liu","year":"2015","unstructured":"Liu G (2015) Pathological brain detection in MRI scanning by wavelet packet Tsallis entropy and fuzzy support vector machine. SpringerPlus 4(1):716","journal-title":"SpringerPlus"},{"issue":"5","key":"5023_CR15","doi-asserted-by":"crossref","first-page":"1218","DOI":"10.1166\/jmihi.2016.1901","volume":"6","author":"Z Lu","year":"2016","unstructured":"Lu Z (2016) A Pathological Brain Detection System Based on Radial Basis Function Neural Network. Journal of Medical Imaging and Health Informatics 6(5):1218\u20131222","journal-title":"Journal of Medical Imaging and Health Informatics"},{"key":"5023_CR16","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1016\/j.csl.2017.01.009","volume":"44","author":"S Mavaddaty","year":"2017","unstructured":"Mavaddaty S, Ahadi SM, Seyedin S (2017) Speech enhancement using sparse dictionary learning in wavelet packet transform domain. Computer Speech And Language 44:22\u201347","journal-title":"Computer Speech And Language"},{"issue":"1","key":"5023_CR17","first-page":"61","volume":"8","author":"N Mustafa","year":"2017","unstructured":"Mustafa N, Memon RA, Li JP et al (2017) A Classification Model for Imbalanced Medical Data based on PCA and Farther Distance based Synthetic Minority Oversampling Technique. Int J Adv Comput Sci Appl 8(1):61\u201367","journal-title":"Int J Adv Comput Sci Appl"},{"issue":"2","key":"5023_CR18","doi-asserted-by":"crossref","first-page":"122","DOI":"10.2174\/1871527315666161024142036","volume":"16","author":"DR Nayak","year":"2017","unstructured":"Nayak DR (2017) Detection of unilateral hearing loss by Stationary Wavelet Entropy. CNS Neurol Disord Drug Targets 16(2):122\u2013128","journal-title":"CNS Neurol Disord Drug Targets"},{"issue":"2","key":"5023_CR19","doi-asserted-by":"crossref","first-page":"1106","DOI":"10.3906\/elk-1507-190","volume":"25","author":"O Oyedotun","year":"2017","unstructured":"Oyedotun O, Khashman A (2017) Iris nevus diagnosis: convolutional neural network and deep belief network. Turk J Electr Eng Comput Sci 25(2):1106\u20131115","journal-title":"Turk J Electr Eng Comput Sci"},{"key":"5023_CR20","doi-asserted-by":"crossref","first-page":"58","DOI":"10.1016\/j.bspc.2015.05.014","volume":"21","author":"P Phillips","year":"2015","unstructured":"Phillips P, Dong Z, Ji G et al (2015) Detection of Alzheimer\u2019s disease and mild cognitive impairment based on structural volumetric MR images using 3D\u2013DWT and WTA-KSVM trained by PSOTVAC. Biomed Signal Process Control 21:58\u201373","journal-title":"Biomed Signal Process Control"},{"key":"5023_CR21","doi-asserted-by":"crossref","first-page":"41","DOI":"10.2528\/PIER15040602","volume":"152","author":"P Phillips","year":"2015","unstructured":"Phillips P, Dong Z, Yang J (2015) Pathological brain detection in magnetic resonance imaging scanning by wavelet entropy and hybridization of biogeography-based optimization and particle swarm optimization. Prog Electromagn Res 152:41\u201358","journal-title":"Prog Electromagn Res"},{"issue":"3","key":"5023_CR22","doi-asserted-by":"crossref","first-page":"303","DOI":"10.1016\/j.cad.2010.12.015","volume":"43","author":"RV Rao","year":"2011","unstructured":"Rao RV, Savsani VJ, Vakharia DP (2011) Teaching-learning-based optimization: A novel method for constrained mechanical design optimization problems. Comput Aided Des 43(3):303\u2013315","journal-title":"Comput Aided Des"},{"issue":"9\u201312","key":"5023_CR23","doi-asserted-by":"crossref","first-page":"2943","DOI":"10.1007\/s00170-016-8649-6","volume":"87","author":"YM Rong","year":"2016","unstructured":"Rong YM, Zhang GJ, Chang Y et al (2016) Integrated optimization model of laser brazing by extreme learning machine and genetic algorithm. Int J Adv Manuf Technol 87(9\u201312):2943\u20132950","journal-title":"Int J Adv Manuf Technol"},{"issue":"s1","key":"5023_CR24","first-page":"1283","volume":"26","author":"P Sun","year":"2015","unstructured":"Sun P (2015) Pathological brain detection based on wavelet entropy and Hu moment invariants. Biomed Mater Eng 26(s1):1283\u20131290","journal-title":"Biomed Mater Eng"},{"issue":"7","key":"5023_CR25","volume":"40","author":"Y Sun","year":"2016","unstructured":"Sun Y (2016) A Multilayer Perceptron Based Smart Pathological Brain Detection System by Fractional Fourier Entropy. J Med Syst 40(7):173","journal-title":"J Med Syst"},{"issue":"3","key":"5023_CR26","doi-asserted-by":"crossref","first-page":"257","DOI":"10.1140\/epja\/i2009-10799-0","volume":"40","author":"C Tsallis","year":"2009","unstructured":"Tsallis C (2009) Nonadditive entropy: The concept and its use. Eur Phys J A 40(3):257\u2013266","journal-title":"Eur Phys J A"},{"key":"5023_CR27","doi-asserted-by":"publisher","unstructured":"Wang H, Lv Y (2016) Smart pathological brain detection system by predator-prey particle swarm optimization and single-hidden layer neural-network. Multimed Tools Appl. doi: 10.1007\/s11042-016-4242-0 (Online)","DOI":"10.1007\/s11042-016-4242-0"},{"issue":"11","key":"5023_CR28","doi-asserted-by":"crossref","first-page":"3068","DOI":"10.1109\/TKDE.2016.2580138","volume":"28","author":"M Wang","year":"2016","unstructured":"Wang M, Li H, Cui JT et al (2016) PINOCCHIO: Probabilistic Influence-Based Location Selection over Moving Objects. IEEE Trans Knowl Data Eng 28(11):3068\u20133082","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"5023_CR29","doi-asserted-by":"crossref","first-page":"373","DOI":"10.1016\/j.jhydrol.2016.10.013","volume":"543","author":"B Yadav","year":"2016","unstructured":"Yadav B, Ch S, Mathur S et al (2016) Estimation of in-situ bioremediation system cost using a hybrid Extreme Learning Machine (ELM)-particle swarm optimization approach. J Hydrol 543:373\u2013385","journal-title":"J Hydrol"},{"issue":"4","key":"5023_CR30","doi-asserted-by":"crossref","first-page":"1795","DOI":"10.3390\/e17041734","volume":"17","author":"J Yang","year":"2015","unstructured":"Yang J (2015) Preclinical diagnosis of magnetic resonance (MR) brain images via discrete wavelet packet transform with Tsallis entropy and generalized eigenvalue proximal support vector machine (GEPSVM). Entropy 17(4):1795\u20131813","journal-title":"Entropy"},{"issue":"10","key":"5023_CR31","doi-asserted-by":"crossref","first-page":"6663","DOI":"10.3390\/e17107101","volume":"17","author":"J Yang","year":"2015","unstructured":"Yang J (2015) Identification of green, Oolong and black teas in China via wavelet packet entropy and fuzzy support vector machine. Entropy 17(10):6663\u20136682","journal-title":"Entropy"},{"issue":"6","key":"5023_CR32","volume":"6","author":"M Yang","year":"2016","unstructured":"Yang M (2016) Dual-Tree Complex Wavelet Transform and Twin Support Vector Machine for Pathological Brain Detection. Appl Sci 6(6):169","journal-title":"Appl Sci"},{"key":"5023_CR33","doi-asserted-by":"crossref","unstructured":"Ying ZB, Li H, Ma JF et al (2016) Adaptively secure ciphertext-policy attribute-based encryption with dynamic policy updating. Science China-Information Sciences 59(4):16, 042701","DOI":"10.1007\/s11432-015-5428-1"},{"key":"5023_CR34","unstructured":"Yuan TF (2015) Detection of subjects and brain regions related to Alzheimer\u2019s disease using 3D MRI scans based on eigenbrain and machine learning. Front Comput Neurosci 9:66"},{"key":"5023_CR35","doi-asserted-by":"crossref","first-page":"344","DOI":"10.1016\/j.eswa.2016.10.048","volume":"72","author":"T Yuksel","year":"2017","unstructured":"Yuksel T (2017) Intelligent visual servoing with extreme learning machine and fuzzy logic. Expert Syst Appl 72:344\u2013356","journal-title":"Expert Syst Appl"},{"key":"5023_CR36","doi-asserted-by":"crossref","first-page":"105","DOI":"10.2528\/PIER16070801","volume":"156","author":"T Zhan","year":"2016","unstructured":"Zhan T (2016) Pathological brain detection by artificial intelligence in magnetic resonance imaging scanning. Prog Electromagn Res 156:105\u2013133","journal-title":"Prog Electromagn Res"},{"issue":"9","key":"5023_CR37","doi-asserted-by":"crossref","first-page":"861","DOI":"10.1177\/0037549716666962","volume":"92","author":"X-X Zhou","year":"2016","unstructured":"Zhou X-X (2016) Comparison of machine learning methods for stationary wavelet entropy-based multiple sclerosis detection: decision tree, k-nearest neighbors, and support vector machine. Simulation 92(9):861\u2013871","journal-title":"Simulation"},{"issue":"3","key":"5023_CR38","doi-asserted-by":"crossref","first-page":"364","DOI":"10.1002\/tee.22226","volume":"11","author":"XX Zhou","year":"2016","unstructured":"Zhou XX, Zhang GS (2016) Detection of abnormal MR brains based on wavelet entropy and feature selection. IEEJ Trans Electr Electron Eng 11(3):364\u2013373","journal-title":"IEEJ Trans Electr Electron Eng"}],"container-title":["Multimedia Tools and Applications"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s11042-017-5023-0\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-017-5023-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-017-5023-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,24]],"date-time":"2025-06-24T14:18:52Z","timestamp":1750774732000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s11042-017-5023-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,7,18]]},"references-count":38,"journal-issue":{"issue":"17","published-print":{"date-parts":[[2018,9]]}},"alternative-id":["5023"],"URL":"https:\/\/doi.org\/10.1007\/s11042-017-5023-0","relation":{},"ISSN":["1380-7501","1573-7721"],"issn-type":[{"value":"1380-7501","type":"print"},{"value":"1573-7721","type":"electronic"}],"subject":[],"published":{"date-parts":[[2017,7,18]]}}}