{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T21:00:37Z","timestamp":1743109237327},"reference-count":19,"publisher":"Springer Science and Business Media LLC","issue":"S4","license":[{"start":{"date-parts":[[2018,12,1]],"date-time":"2018-12-01T00:00:00Z","timestamp":1543622400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["BMC Med Inform Decis Mak"],"published-print":{"date-parts":[[2018,12]]},"DOI":"10.1186\/s12911-018-0676-9","type":"journal-article","created":{"date-parts":[[2018,12,12]],"date-time":"2018-12-12T01:42:10Z","timestamp":1544578930000},"update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Leveraging auxiliary measures: a deep multi-task neural network for predictive modeling in clinical research"],"prefix":"10.1186","volume":"18","author":[{"given":"Xiangrui","family":"Li","sequence":"first","affiliation":[]},{"given":"Dongxiao","family":"Zhu","sequence":"additional","affiliation":[]},{"given":"Phillip","family":"Levy","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2018,12,12]]},"reference":[{"key":"676_CR1","doi-asserted-by":"crossref","unstructured":"Cho K, Van Merri\u00ebnboer B, Gulcehre C, Bahdanau D, Bougares F, Schwenk H, et al.Learning phrase representations using RNN encoder-decoder for statistical machine translation; 2014. arXiv preprint arXiv:061078.","DOI":"10.3115\/v1\/D14-1179"},{"key":"676_CR2","unstructured":"Krizhevsky A, Sutskever I, Hinton GE. Imagenet classification with deep convolutional neural networks. In: Advances in neural information processing systems. 2012. p. 1097\u2013105."},{"key":"676_CR3","volume-title":"2016 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","author":"MZ Nezhad","year":"2016","unstructured":"Nezhad MZ, Zhu D, Li X, Yang K, Levy P. Safs: A deep feature selection approach for precision medicine. In: 2016 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). Shenzhen: IEEE: 2016. p. 501\u20136."},{"issue":"2","key":"676_CR4","doi-asserted-by":"crossref","first-page":"361","DOI":"10.1093\/jamia\/ocw112","volume":"24","author":"E Choi","year":"2016","unstructured":"Choi E, Schuetz A, Stewart WF, Sun J. Using recurrent neural network models for early detection of heart failure onset. J Am Med Inform Assoc. 2016; 24(2):361\u201370.","journal-title":"J Am Med Inform Assoc"},{"key":"676_CR5","volume-title":"Deep learning","author":"I Goodfellow","year":"2016","unstructured":"Goodfellow I, Bengio Y, Courville A, Bengio Y. Deep learning. Cambridge: MIT press; 2016."},{"key":"676_CR6","volume-title":"2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","author":"X Li","year":"2017","unstructured":"Li X, Zhu D, Levy P. Predictive deep network with leveraging clinical measure as auxiliary task. In: 2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). Kansas City: IEEE: 2017. p. 786\u201391."},{"key":"676_CR7","doi-asserted-by":"crossref","unstructured":"Caruana R. Multitask learning. In: Learning to learn.1998. p. 95\u2013133.","DOI":"10.1007\/978-1-4615-5529-2_5"},{"key":"676_CR8","unstructured":"Ruder S. An Overview of Multi-Task Learning in Deep Neural Networks; 2017. arXiv preprint arXiv: 605098."},{"key":"676_CR9","unstructured":"Zhang Y, Yang Q. A Surey on Multi-Task Learning. 2017. arXiv preprint arXiv: 708114."},{"key":"676_CR10","volume-title":"Multi-task Survival Analysis. 2017 IEEE International Conference on Data Mining (ICDM)","author":"L Wang","year":"2018","unstructured":"Wang L, Li Y, Zhou J, Zhu D, Ye J. Multi-task Survival Analysis. 2017 IEEE International Conference on Data Mining (ICDM). New Orleans: IEEE; 2018, pp. 485\u201394."},{"issue":"02","key":"676_CR11","doi-asserted-by":"publisher","first-page":"209","DOI":"10.1142\/S0129065797000227","volume":"8","author":"TD Gedeon","year":"1997","unstructured":"Gedeon TD. Data mining of inputs: analysing magnitude and functional measures. Int J Neural Syst. 1997; 8(02):209\u201318.","journal-title":"Int J Neural Syst"},{"key":"676_CR12","unstructured":"Dheeru D, Karra Taniskidou E. UCI Machine Learning Repository. 2017. http:\/\/archive.ics.uci.edu\/ml ."},{"key":"676_CR13","first-page":"2825","volume":"12","author":"F Pedregosa","year":"2011","unstructured":"Pedregosa F, Varoquaux G, Gramfort A, Michel V, Thirion B, Grisel O, et al.Scikit-learn: Machine Learning in Python. J Mach Learn Res. 2011; 12:2825\u201330.","journal-title":"J Mach Learn Res"},{"key":"676_CR14","unstructured":"Pytorch. http:\/\/pytorch.org . Accessed date: 30 July 2017."},{"issue":"1","key":"676_CR15","doi-asserted-by":"publisher","first-page":"85","DOI":"10.5152\/balkanmedj.2012.097","volume":"30","author":"A Helvac\u0131","year":"2013","unstructured":"Helvac\u0131 A, \u00c7opur B, Ada\u015f M. Correlation between Left Ventricular Mass Index and Calcium Metabolism in Patients with Essential Hypertension. Balkan Med J. 2013; 30(1):85.","journal-title":"Balkan Med J"},{"issue":"1","key":"676_CR16","doi-asserted-by":"publisher","first-page":"43","DOI":"10.1186\/s12933-015-0200-9","volume":"14","author":"J Li","year":"2015","unstructured":"Li J, Wu N, Li Y, Ye K, He M, Hu R. Cross-sectional analysis of serum calcium levels for associations with left ventricular hypertrophy in normocalcemia individuals with type 2 diabetes. Cardiovasc Diabetol. 2015; 14(1):43.","journal-title":"Cardiovasc Diabetol"},{"issue":"3","key":"676_CR17","doi-asserted-by":"publisher","first-page":"470","DOI":"10.1161\/01.CIR.68.3.470","volume":"68","author":"RB Devereux","year":"1983","unstructured":"Devereux RB, Pickering TG, Harshfield GA, Kleinert HD, Denby L, Clark L, et al.Left ventricular hypertrophy in patients with hypertension: importance of blood pressure response to regularly recurring stress. Circulation. 1983; 68(3):470\u20136.","journal-title":"Circulation"},{"issue":"3","key":"676_CR18","doi-asserted-by":"publisher","first-page":"845","DOI":"10.1161\/01.HYP.37.3.845","volume":"37","author":"AH El-Gharbawy","year":"2001","unstructured":"El-Gharbawy AH, Nadig VS, Kotchen JM, Grim CE, Sagar KB, Kaldunski M, et al.Arterial pressure, left ventricular mass, and aldosterone in essential hypertension. Hypertension. 2001; 37(3):845\u201350.","journal-title":"Hypertension"},{"issue":"3","key":"676_CR19","doi-asserted-by":"publisher","first-page":"321","DOI":"10.1046\/j.1365-2265.1999.00651.x","volume":"50","author":"A Piovesan","year":"1999","unstructured":"Piovesan A, Molineri N, Casasso F, Emmolo I, Ugliengo G, Cesario F, et al.Left ventricular hypertrophy in primary hyperparathyroidism. Effects of successful parathyroidectomy. Clin Endocrinol. 1999; 50(3):321\u20138.","journal-title":"Clin Endocrinol"}],"container-title":["BMC Medical Informatics and Decision Making"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1186\/s12911-018-0676-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1186\/s12911-018-0676-9\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1186\/s12911-018-0676-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,11,17]],"date-time":"2020-11-17T10:18:44Z","timestamp":1605608324000},"score":1,"resource":{"primary":{"URL":"https:\/\/bmcmedinformdecismak.biomedcentral.com\/articles\/10.1186\/s12911-018-0676-9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,12]]},"references-count":19,"journal-issue":{"issue":"S4","published-print":{"date-parts":[[2018,12]]}},"alternative-id":["676"],"URL":"https:\/\/doi.org\/10.1186\/s12911-018-0676-9","relation":{},"ISSN":["1472-6947"],"issn-type":[{"value":"1472-6947","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,12]]},"assertion":[{"value":"12 December 2018","order":1,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"Not applicable.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"Not applicable.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"The authors declare that they have no competing interests.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}},{"value":"Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Publisher\u2019s Note"}}],"article-number":"126"}}