{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,20]],"date-time":"2026-02-20T16:49:26Z","timestamp":1771606166034,"version":"3.50.1"},"reference-count":21,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2019,12,1]],"date-time":"2019-12-01T00:00:00Z","timestamp":1575158400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2019,12,30]],"date-time":"2019-12-30T00:00:00Z","timestamp":1577664000000},"content-version":"vor","delay-in-days":29,"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":[[2019,12]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Background<\/jats:title><jats:p>Patient stratification is a critical task in clinical decision making since it can allow physicians to choose treatments in a personalized way. Given the increasing availability of electronic medical records (EMRs) with longitudinal data, one crucial problem is how to efficiently cluster the patients based on the temporal information from medical appointments. In this work, we propose applying the Temporal Needleman-Wunsch (TNW) algorithm to align discrete sequences with the transition time information between symbols. These symbols may correspond to a patient\u2019s current therapy, their overall health status, or any other discrete state. The transition time information represents the duration of each of those states. The obtained TNW pairwise scores are then used to perform hierarchical clustering. To find the best number of clusters and assess their stability, a resampling technique is applied.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>We propose the AliClu, a novel tool for clustering temporal clinical data based on the TNW algorithm coupled with clustering validity assessments through bootstrapping. The AliClu was applied for the analysis of the rheumatoid arthritis EMRs obtained from the Portuguese database of rheumatologic patient visits (Reuma.pt). In particular, the AliClu was used for the analysis of therapy switches, which were coded as letters corresponding to biologic drugs and included their durations before each change occurred. The obtained optimized clusters allow one to stratify the patients based on their temporal therapy profiles and to support the identification of common features for those groups.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>The AliClu is a promising computational strategy to analyse longitudinal patient data by providing validated clusters and by unravelling the patterns that exist in clinical outcomes. Patient stratification is performed in an automatic or semi-automatic way, allowing one to tune the alignment, clustering, and validation parameters. The AliClu is freely available at<jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" ext-link-type=\"uri\" xlink:href=\"https:\/\/github.com\/sysbiomed\/AliClu\">https:\/\/github.com\/sysbiomed\/AliClu<\/jats:ext-link>.<\/jats:p><\/jats:sec>","DOI":"10.1186\/s12911-019-1013-7","type":"journal-article","created":{"date-parts":[[2019,12,30]],"date-time":"2019-12-30T22:02:51Z","timestamp":1577743371000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["AliClu - Temporal sequence alignment for clustering longitudinal clinical data"],"prefix":"10.1186","volume":"19","author":[{"given":"Kishan","family":"Rama","sequence":"first","affiliation":[]},{"given":"Helena","family":"Canh\u00e3o","sequence":"additional","affiliation":[]},{"given":"Alexandra M.","family":"Carvalho","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1954-5487","authenticated-orcid":false,"given":"Susana","family":"Vinga","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2019,12,30]]},"reference":[{"key":"1013_CR1","doi-asserted-by":"publisher","unstructured":"Syed H, Das AK. Temporal Needleman-Wunsch. In: 2015 IEEE International Conference on Data Science and Advanced Analytics (DSAA). IEEE: 2015. https:\/\/doi.org\/10.1109\/dsaa.2015.7344785.","DOI":"10.1109\/dsaa.2015.7344785"},{"key":"1013_CR2","doi-asserted-by":"publisher","first-page":"443","DOI":"10.1016\/0022-2836(70)90057-4","volume":"48","author":"SB Needleman","year":"1970","unstructured":"Needleman SB, Wunsch CD. A General Method Applicable to the Search for Similarities in the Amino Acid Sequence of Two Proteins. J Mol Biol. 1970; 48:443\u201353.","journal-title":"J Mol Biol"},{"key":"1013_CR3","doi-asserted-by":"publisher","first-page":"43","DOI":"10.1109\/TASSP.1978.1163055","volume":"26","author":"H Sakoe","year":"1978","unstructured":"Sakoe H, Chiba S. Dynamic programming algorithm optimization for spoken word recognition. IEEE Trans Acoust Speech Sig Process. 1978; 26:43\u20139.","journal-title":"IEEE Trans Acoust Speech Sig Process"},{"key":"1013_CR4","volume-title":"Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009","author":"F Zhou","year":"2009","unstructured":"Zhou F, la Torre FD. Canonical time warping for alignment of human behavior. In: Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Vancouver: Curran Associates, Inc.: 2009. p. 2286\u201394."},{"issue":"1","key":"1013_CR5","doi-asserted-by":"publisher","first-page":"90","DOI":"10.1007\/s11263-014-0758-9","volume":"112","author":"K Kulkarni","year":"2015","unstructured":"Kulkarni K, Evangelidis G, Cech J, Horaud R. Continuous action recognition based on sequence alignment. Int J Comput Vis. 2015; 112(1):90\u2013114. https:\/\/doi.org\/10.1007\/s11263-014-0758-9.","journal-title":"Int J Comput Vis"},{"issue":"10","key":"1013_CR6","doi-asserted-by":"publisher","first-page":"4","DOI":"10.1186\/1471-2105-8-S10-S4","volume":"8","author":"B Fischer","year":"2007","unstructured":"Fischer B, Roth V, Buhmann JM. Time-series alignment by non-negative multiple generalized canonical correlation analysis. BMC Bioinformatics. 2007; 8(10):4.","journal-title":"BMC Bioinformatics"},{"issue":"1","key":"1013_CR7","doi-asserted-by":"publisher","first-page":"539","DOI":"10.1038\/msb.2011.75","volume":"7","author":"F Sievers","year":"2011","unstructured":"Sievers F, Wilm A, Dineen D, Gibson TJ, Karplus K, Li W, Lopez R, McWilliam H, Remmert M, S\u00f6ding J, Thompson JD, Higgins DG. Fast, scalable generation of high-quality protein multiple sequence alignments using clustal omega. Mol Syst Biol. 2011; 7(1):539.","journal-title":"Mol Syst Biol"},{"issue":"4","key":"1013_CR8","doi-asserted-by":"publisher","first-page":"772","DOI":"10.1093\/molbev\/mst010","volume":"30","author":"K Katoh","year":"2013","unstructured":"Katoh K, Standley DM. Mafft multiple sequence alignment software version 7: Improvements in performance and usability. Mol Biol Evol. 2013; 30(4):772\u201380.","journal-title":"Mol Biol Evol"},{"issue":"5","key":"1013_CR9","doi-asserted-by":"publisher","first-page":"1792","DOI":"10.1093\/nar\/gkh340","volume":"32","author":"RC Edgar","year":"2004","unstructured":"Edgar RC. Muscle: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res. 2004; 32(5):1792\u20137.","journal-title":"Nucleic Acids Res"},{"issue":"9","key":"1013_CR10","doi-asserted-by":"publisher","first-page":"755","DOI":"10.1093\/bioinformatics\/14.9.755","volume":"14","author":"SR Eddy","year":"1998","unstructured":"Eddy SR. Profile hidden Markov models,. Bioinformatics. 1998; 14(9):755\u201363. https:\/\/doi.org\/10.1093\/bioinformatics\/14.9.755.","journal-title":"Bioinformatics"},{"issue":"1","key":"1013_CR11","first-page":"45","volume":"36","author":"H Canh\u00e3o","year":"2011","unstructured":"Canh\u00e3o H, Faustino A, Martins F, et al.Reuma.pt - The Rheumatic Diseases Portuguese Register. Acta Reumatologica Portuguesa. 2011; 36(1):45\u201356.","journal-title":"Acta Reumatologica Portuguesa"},{"issue":"9","key":"1013_CR12","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1371\/journal.pone.0074873","volume":"8","author":"E. Docampo","year":"2013","unstructured":"Docampo E., Collado A., Escaram\u00eds G, Carbonell J, Rivera J, Vidal J, Alegre J, Rabionet R, Estivill X. Cluster analysis of clinical data identifies fibromyalgia subgroups. PLOS ONE. 2013; 8(9):1\u20137. https:\/\/doi.org\/10.1371\/journal.pone.0074873.","journal-title":"PLOS ONE"},{"issue":"1","key":"1013_CR13","doi-asserted-by":"crossref","first-page":"57","DOI":"10.15388\/Informatica.2011.314","volume":"22","author":"L Garg","year":"2011","unstructured":"Garg L, McClean S, Meenan BJ, Millard P. Phase-type survival trees and mixed distribution survival trees for clustering patients\u2019 hospital length of stay. Informatica. 2011; 22(1):57\u201372.","journal-title":"Informatica"},{"issue":"1","key":"1013_CR14","doi-asserted-by":"publisher","first-page":"99","DOI":"10.1186\/1471-2474-12-99","volume":"12","author":"I Ax\u00e9n","year":"2011","unstructured":"Ax\u00e9n I, Bodin L., Bergstr\u00f6m G, Halasz L, Lange F, L\u00f6vgren PW, Rosenbaum A, Leboeuf-Yde C, Jensen I. Clustering patients on the basis of their individual course of low back pain over a six month period. BMC Musculoskelet Disord. 2011; 12(1):99. https:\/\/doi.org\/10.1186\/1471-2474-12-99.","journal-title":"BMC Musculoskelet Disord"},{"issue":"3","key":"1013_CR15","doi-asserted-by":"publisher","first-page":"1441","DOI":"10.1016\/j.csda.2007.04.005","volume":"52","author":"R De la Cruz-Mes\u00eda","year":"2008","unstructured":"De la Cruz-Mes\u00eda R, Quintana FA, Marshall G. Model-based clustering for longitudinal data. Comput Stat Data Anal. 2008; 52(3):1441\u201357. https:\/\/doi.org\/10.1016\/j.csda.2007.04.005.","journal-title":"Comput Stat Data Anal"},{"key":"1013_CR16","doi-asserted-by":"publisher","first-page":"664","DOI":"10.1016\/j.neucom.2017.06.053","volume":"267","author":"A Saxena","year":"2017","unstructured":"Saxena A, Prasad M, Gupta A, Bharill N, Patel OP, Tiwari A, Er MJ, Ding W, Lin C-T. A review of clustering techniques and developments. Neurocomputing. 2017; 267:664\u201381.","journal-title":"Neurocomputing"},{"key":"1013_CR17","doi-asserted-by":"crossref","unstructured":"Mucha H-J. Advances in Data Analysis In: Decker R, Lenz H-J, editors. Berlin, Heidelberg: Springer: 2007. p. 115\u2013122.","DOI":"10.1007\/978-3-540-70981-7_14"},{"key":"1013_CR18","doi-asserted-by":"publisher","first-page":"846","DOI":"10.1080\/01621459.1971.10482356","volume":"66","author":"W M. Rand","year":"1971","unstructured":"M. Rand W. Objective criteria for the evaluation of clustering methods. J Am Stat Assoc. 1971; 66:846\u201350.","journal-title":"J Am Stat Assoc"},{"issue":"1","key":"1013_CR19","doi-asserted-by":"publisher","first-page":"193","DOI":"10.1007\/BF01908075","volume":"2","author":"L Hubert","year":"1985","unstructured":"Hubert L, Arabie P. Comparing partitions. J Classif. 1985; 2(1):193\u2013218.","journal-title":"J Classif"},{"key":"1013_CR20","doi-asserted-by":"publisher","first-page":"553","DOI":"10.1080\/01621459.1983.10478008","volume":"78","author":"E B. Fowlkes","year":"1983","unstructured":"B. Fowlkes E, Mallows C. A method for comparing two hierachical clusterings. J Am Stat Assoc. 1983; 78:553\u201369.","journal-title":"J Am Stat Assoc"},{"key":"1013_CR21","first-page":"569","volume":"78","author":"DL Wallace","year":"1983","unstructured":"Wallace DL. A method for comparing two hierachical clusterings: Comment. J Am Stat Assoc. 1983; 78:569\u201376.","journal-title":"J Am Stat Assoc"}],"container-title":["BMC Medical Informatics and Decision Making"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1186\/s12911-019-1013-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1186\/s12911-019-1013-7\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1186\/s12911-019-1013-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,10,9]],"date-time":"2022-10-09T14:58:57Z","timestamp":1665327537000},"score":1,"resource":{"primary":{"URL":"https:\/\/bmcmedinformdecismak.biomedcentral.com\/articles\/10.1186\/s12911-019-1013-7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,12]]},"references-count":21,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2019,12]]}},"alternative-id":["1013"],"URL":"https:\/\/doi.org\/10.1186\/s12911-019-1013-7","relation":{},"ISSN":["1472-6947"],"issn-type":[{"value":"1472-6947","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,12]]},"assertion":[{"value":"24 June 2019","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"19 December 2019","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"30 December 2019","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"Reuma.pt was approved by the National Data Protection Board (Comiss\u00e3o Nacional de Prote\u00e7\u00e3o de Dados \u2013 CNPD, Portugal) and by the Ethics Committee of Centro Hospitalar Lisboa Norte (CHLN) - Hospital de Santa Maria (HSM), Lisbon, Portugal. Patients signed Reuma.pt\u2019s informed and written consent.","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":"SV is member of the Editorial Board of BMC Bioinformatics. KR, HC, and AMC declare that they have no competing interests.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"289"}}