{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,13]],"date-time":"2026-01-13T21:00:04Z","timestamp":1768338004051,"version":"3.49.0"},"reference-count":31,"publisher":"Springer Science and Business Media LLC","issue":"10","license":[{"start":{"date-parts":[[2017,9,11]],"date-time":"2017-09-11T00:00:00Z","timestamp":1505088000000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Med Syst"],"published-print":{"date-parts":[[2017,10]]},"DOI":"10.1007\/s10916-017-0814-4","type":"journal-article","created":{"date-parts":[[2017,9,11]],"date-time":"2017-09-11T19:45:45Z","timestamp":1505159145000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":30,"title":["Three-Category Classification of Magnetic Resonance Hearing Loss Images Based on Deep Autoencoder"],"prefix":"10.1007","volume":"41","author":[{"given":"Wenjuan","family":"Jia","sequence":"first","affiliation":[]},{"given":"Ming","family":"Yang","sequence":"additional","affiliation":[]},{"given":"Shui-Hua","family":"Wang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2017,9,11]]},"reference":[{"issue":"5","key":"814_CR1","doi-asserted-by":"crossref","first-page":"1181","DOI":"10.1002\/lary.26322","volume":"127","author":"NS Patel","year":"2017","unstructured":"Patel, N.S., Hunter, J.B., O'Connell, B.P., et al., Risk of progressive hearing loss in untreated superior semicircular canal dehiscence. Laryngoscope. 127(5):1181\u20131186, 2017.","journal-title":"Laryngoscope"},{"key":"814_CR2","doi-asserted-by":"crossref","first-page":"129","DOI":"10.1016\/j.heares.2016.11.013","volume":"349","author":"A Kurabi","year":"2017","unstructured":"Kurabi, A., Keithley, E.M., Housley, G.D., et al., Cellular mechanisms of noise-induced hearing loss. Hear. Res. 349:129\u2013137, 2017.","journal-title":"Hear. Res."},{"issue":"6","key":"814_CR3","doi-asserted-by":"crossref","first-page":"892","DOI":"10.1111\/cge.12915","volume":"91","author":"C Neuhaus","year":"2017","unstructured":"Neuhaus, C., Lang-Roth, R., Zimmermann, U., et al., Extension of the clinical and molecular phenotype of DIAPH1-associated autosomal dominant hearing loss (DFNA1). Clin. Genet. 91(6):892\u2013901, 2017.","journal-title":"Clin. Genet."},{"issue":"1","key":"814_CR4","doi-asserted-by":"crossref","first-page":"229","DOI":"10.1002\/lary.26190","volume":"127","author":"M Etminan","year":"2017","unstructured":"Etminan, M., Westerberg, B.D., Kozak, F.K., et al., Risk of sensorineural hearing loss with macrolide antibiotics: A nested case-control study. Laryngoscope. 127(1):229\u2013232, 2017.","journal-title":"Laryngoscope"},{"key":"814_CR5","doi-asserted-by":"crossref","first-page":"87","DOI":"10.1016\/j.neurobiolaging.2017.04.003","volume":"56","author":"EJ Brecht","year":"2017","unstructured":"Brecht, E.J., Barsz, K., Gross, B., et al., Increasing GABA reverses age-related alterations in excitatory receptive fields and intensity coding of auditory midbrain neurons in aged mice. Neurobiol. Aging. 56:87\u201399, 2017.","journal-title":"Neurobiol. Aging"},{"key":"814_CR6","doi-asserted-by":"crossref","first-page":"187","DOI":"10.1016\/j.ymssp.2017.03.034","volume":"95","author":"H Shao","year":"2017","unstructured":"Shao, H., Jiang, H., Zhao, H., et al., A novel deep autoencoder feature learning method for rotating machinery fault diagnosis. Mech. Syst.Signal Process. 95:187\u2013204, 2017.","journal-title":"Mech. Syst.Signal Process."},{"key":"814_CR7","doi-asserted-by":"crossref","unstructured":"Li, J., Detection of left-sided and right-sided hearing loss via fractional fourier transform. Entropy 18(5):Article ID: 194, 2016.","DOI":"10.3390\/e18050194"},{"issue":"2","key":"814_CR8","doi-asserted-by":"crossref","first-page":"122","DOI":"10.2174\/1871527315666161024142036","volume":"16","author":"DR Nayak","year":"2017","unstructured":"Nayak, D.R., Detection of unilateral hearing loss by stationary wavelet entropy. CNS Neurol. Disord. - Drug Targets. 16(2):122\u2013128, 2017.","journal-title":"CNS Neurol. Disord. - Drug Targets"},{"key":"814_CR9","doi-asserted-by":"publisher","unstructured":"Chen, Y., and Chen, X.-Q, Sensorineural hearing loss detection via discrete wavelet transform and principal component analysis combined with generalized eigenvalue proximal support vector machine and Tikhonov regularization. Multimed. Tools Appl. 2016 doi: https:\/\/doi.org\/10.1007\/s11042-016-4087-6","DOI":"10.1007\/s11042-016-4087-6"},{"issue":"1\u20134","key":"814_CR10","first-page":"505","volume":"151","author":"J Li","year":"2017","unstructured":"Li, J., Texture analysis method based on fractional Fourier entropy and fitness-scaling adaptive genetic algorithm for detecting left-sided and right-sided sensorineural hearing loss. Fundam. Inf. 151(1\u20134):505\u2013521, 2017.","journal-title":"Fundam. Inf."},{"key":"814_CR11","doi-asserted-by":"crossref","unstructured":"Lu, H. Hearing loss detection in medical multimedia data by discrete wavelet packet entropy and single-hidden layer neural network trained by adaptive learning-rate back propagation. In 14th International Symposium on Neural Networks (ISNN). Sapporo, Japan: Springer. pp 541\u2013549, 2017.","DOI":"10.1007\/978-3-319-59081-3_63"},{"key":"814_CR12","doi-asserted-by":"crossref","first-page":"171","DOI":"10.1016\/j.eswa.2017.05.017","volume":"84","author":"X Gao","year":"2017","unstructured":"Gao, X., Sun, Q., and Xu, H., Multiple-rank supervised canonical correlation analysis for feature extraction, fusion and recognition. Expert Syst. Appl. 84:171\u2013185, 2017.","journal-title":"Expert Syst. Appl."},{"key":"814_CR13","doi-asserted-by":"crossref","first-page":"2","DOI":"10.1016\/j.foodchem.2017.03.056","volume":"236","author":"R Kovrlija","year":"2017","unstructured":"Kovrlija, R., and Rondeau-Mouro, C., Multi-scale NMR and MRI approaches to characterize starchy products. Food Chem. 236:2\u201314, 2017.","journal-title":"Food Chem."},{"key":"814_CR14","doi-asserted-by":"crossref","first-page":"225","DOI":"10.1016\/j.cam.2017.04.040","volume":"324","author":"JC Cort\u00e9s","year":"2017","unstructured":"Cort\u00e9s, J.C., Navarro-Quiles, A., Romero, J.V., et al., Randomizing the parameters of a Markov chain to model the stroke disease: A technical generalization of established computational methodologies towards improving real applications. J. Comput. Appl. Math. 324:225\u2013240, 2017.","journal-title":"J. Comput. Appl. Math."},{"key":"814_CR15","doi-asserted-by":"crossref","first-page":"12","DOI":"10.1016\/j.neucom.2017.02.066","volume":"243","author":"Z Fan","year":"2017","unstructured":"Fan, Z., Bi, D., He, L., et al., Low-level structure feature extraction for image processing via stacked sparse denoising autoencoder. Neurocomputing. 243:12\u201320, 2017.","journal-title":"Neurocomputing"},{"key":"814_CR16","doi-asserted-by":"crossref","first-page":"149","DOI":"10.1016\/j.cam.2017.04.045","volume":"325","author":"N Andrei","year":"2017","unstructured":"Andrei, N., Accelerated adaptive Perry conjugate gradient algorithms based on the self-scaling memoryless BFGS update. J. Comput. Appl. Math. 325:149\u2013164, 2017.","journal-title":"J. Comput. Appl. Math."},{"key":"814_CR17","doi-asserted-by":"crossref","unstructured":"Le, M. H., Chen, J., Wang, L., et al., Automated diagnosis of prostate cancer in multi-parametric MRI based on multimodal convolutional neural networks. Phys. Med. Biol. 62(16):6497\u20136514, 2017.","DOI":"10.1088\/1361-6560\/aa7731"},{"issue":"1","key":"814_CR18","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1016\/j.acha.2015.09.007","volume":"43","author":"WB March","year":"2017","unstructured":"March, W.B., and Biros, G., Far-field compression for fast kernel summation methods in high dimensions. Appl. Comput. Harmon. Anal. 43(1):39\u201375, 2017.","journal-title":"Appl. Comput. Harmon. Anal."},{"key":"814_CR19","doi-asserted-by":"crossref","first-page":"149","DOI":"10.1016\/j.csl.2017.01.007","volume":"45","author":"H Choi","year":"2017","unstructured":"Choi, H., Cho, K., and Bengio, Y., Context-dependent word representation for neural machine translation. Comput. Speech Lang. 45:149\u2013160, 2017.","journal-title":"Comput. Speech Lang."},{"key":"814_CR20","doi-asserted-by":"crossref","first-page":"64","DOI":"10.1016\/j.imavis.2017.01.005","volume":"60","author":"A Sankaran","year":"2017","unstructured":"Sankaran, A., Vatsa, M., Singh, R., et al., Group sparse autoencoder. Image Vis. Comput. 60:64\u201374, 2017.","journal-title":"Image Vis. Comput."},{"issue":"2","key":"814_CR21","doi-asserted-by":"crossref","first-page":"387","DOI":"10.1007\/s00180-016-0657-3","volume":"32","author":"AK Ghosh","year":"2016","unstructured":"Ghosh, A.K., and Chakraborty, A., Use of EM algorithm for data reduction under sparsity assumption. Comput. Stat. 32(2):387\u2013407, 2016.","journal-title":"Comput. Stat."},{"issue":"7","key":"814_CR22","doi-asserted-by":"crossref","first-page":"10149","DOI":"10.1007\/s11042-016-3603-z","volume":"76","author":"L Liu","year":"2016","unstructured":"Liu, L., Cheng, D., Tian, F., et al., Active contour driven by multi-scale local binary fitting and Kullback-Leibler divergence for image segmentation. Multimed. Tools Appl. 76(7):10149\u201310168, 2016.","journal-title":"Multimed. Tools Appl."},{"issue":"5","key":"814_CR23","doi-asserted-by":"crossref","first-page":"1401","DOI":"10.1007\/s11222-016-9694-6","volume":"27","author":"B Lin","year":"2016","unstructured":"Lin, B., Wang, Q., Zhang, J., et al., Stable prediction in high-dimensional linear models. Stat. Comput. 27(5):1401\u20131412, 2016.","journal-title":"Stat. Comput."},{"issue":"7","key":"814_CR24","doi-asserted-by":"crossref","first-page":"1336","DOI":"10.1039\/C7MB00188F","volume":"13","author":"YB Wang","year":"2017","unstructured":"Wang, Y.B., You, Z.H., Li, X., et al., Predicting protein-protein interactions from protein sequences by a stacked sparse autoencoder deep neural network. Mol. Biosyst. 13(7):1336\u20131344, 2017.","journal-title":"Mol. Biosyst."},{"issue":"8","key":"814_CR25","doi-asserted-by":"crossref","first-page":"10919","DOI":"10.1007\/s11042-016-3312-7","volume":"76","author":"C Hong","year":"2016","unstructured":"Hong, C., Yu, J., Jane, Y., et al., Three-dimensional image-based human pose recovery with hypergraph regularized autoencoders. Multimed. Tools Appl. 76(8):10919\u201310937, 2016.","journal-title":"Multimed. Tools Appl."},{"key":"814_CR26","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.eswa.2017.04.001","volume":"82","author":"S Zeng","year":"2017","unstructured":"Zeng, S., Gou, J., and Deng, L., An antinoise sparse representation method for robust face recognition via joint l 1 and l 2 regularization. Expert Syst. Appl. 82:1\u20139, 2017.","journal-title":"Expert Syst. Appl."},{"key":"814_CR27","doi-asserted-by":"publisher","unstructured":"Iliadis, L., and Maglogiannis I. (Eds.), Scaled conjugate gradient based adaptive ANN control for SVM-DTC inductionmotor drive. Artif. Intell. Appl. Innov. 384\u2013395, 2016. https:\/\/doi.org\/10.1007\/978-3-319-44944-933 .","DOI":"10.1007\/978-3-319-44944-933"},{"issue":"6","key":"814_CR28","doi-asserted-by":"crossref","DOI":"10.1088\/1361-6501\/aa61b6","volume":"28","author":"A Gholami","year":"2017","unstructured":"Gholami, A., Honarvar, F., and Moghaddam, H.A., Modeling the ultrasonic testing echoes by a combination of particle swarm optimization and Levenberg\u2013Marquardt algorithms. Meas. Sci. Technol. 28(6):065001, 2017.","journal-title":"Meas. Sci. Technol."},{"key":"814_CR29","doi-asserted-by":"crossref","first-page":"535","DOI":"10.1016\/j.asoc.2016.02.039","volume":"43","author":"N Zhang","year":"2016","unstructured":"Zhang, N., Ding, S., and Zhang, J., Multi layer ELM-RBF for multi-label learning. Appl. Soft Comput. 43:535\u2013545, 2016.","journal-title":"Appl. Soft Comput."},{"issue":"12","key":"814_CR30","doi-asserted-by":"crossref","first-page":"2115","DOI":"10.1007\/s11432-008-0124-z","volume":"51","author":"LN Wu","year":"2008","unstructured":"Wu, L.N., Improved image filter based on SPCNN. Sci. China Ser. F-Inf. Sci. 51(12):2115\u20132125, 2008.","journal-title":"Sci. China Ser. F-Inf. Sci."},{"issue":"4","key":"814_CR31","doi-asserted-by":"crossref","first-page":"841","DOI":"10.3390\/e13040841","volume":"13","author":"L Wu","year":"2011","unstructured":"Wu, L., Optimal multi-level thresholding based on maximum Tsallis entropy via an artificial bee Colony approach. Entropy. 13(4):841\u2013859, 2011.","journal-title":"Entropy."}],"updated-by":[{"DOI":"10.1007\/s10916-017-0884-3","type":"correction","label":"Correction","source":"publisher","updated":{"date-parts":[[2018,1,3]],"date-time":"2018-01-03T00:00:00Z","timestamp":1514937600000}}],"container-title":["Journal of Medical Systems"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s10916-017-0814-4\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10916-017-0814-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10916-017-0814-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,10,3]],"date-time":"2019-10-03T10:00:28Z","timestamp":1570096828000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s10916-017-0814-4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,9,11]]},"references-count":31,"journal-issue":{"issue":"10","published-print":{"date-parts":[[2017,10]]}},"alternative-id":["814"],"URL":"https:\/\/doi.org\/10.1007\/s10916-017-0814-4","relation":{"correction":[{"id-type":"doi","id":"10.1007\/s10916-017-0884-3","asserted-by":"object"}]},"ISSN":["0148-5598","1573-689X"],"issn-type":[{"value":"0148-5598","type":"print"},{"value":"1573-689X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2017,9,11]]},"article-number":"165"}}