{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T17:41:09Z","timestamp":1780335669489,"version":"3.54.1"},"reference-count":24,"publisher":"Springer Science and Business Media LLC","issue":"S5","license":[{"start":{"date-parts":[[2023,3,22]],"date-time":"2023-03-22T00:00:00Z","timestamp":1679443200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2023,3,22]],"date-time":"2023-03-22T00:00:00Z","timestamp":1679443200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/501100004663","name":"Ministry of Science and Technology, Taiwan","doi-asserted-by":"publisher","award":["MOST 110-2221-E-037-005"],"award-info":[{"award-number":["MOST 110-2221-E-037-005"]}],"id":[{"id":"10.13039\/501100004663","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["BMC Bioinformatics"],"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Background<\/jats:title><jats:p>Antibiotic resistance has become a global concern. Vancomycin is known as the last line of antibiotics, but its treatment index is narrow. Therefore, clinical dosing decisions must be made with the utmost care; such decisions are said to be \u201csuitable\u201d only when both \u201cefficacy\u201d and \u201csafety\u201d are considered. This study presents a model, namely the \u201censemble strategy model,\u201d to predict the suitability of vancomycin regimens. The experimental data consisted of 2141 \u201csuitable\u201d and \u201cunsuitable\u201d patients tagged with a vancomycin regimen, including six diagnostic input attributes (sex, age, weight, serum creatinine, dosing interval, and total daily dose), and the dataset was normalized into a training dataset, a validation dataset, and a test dataset. AdaBoost.M1, Bagging, fastAdaboost, Neyman\u2013Pearson, and Stacking were used for model training. The \u201censemble strategy concept\u201d was then used to arrive at the final decision by voting to build a model for predicting the suitability of vancomycin treatment regimens.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>The results of the tenfold cross-validation showed that the average accuracy of the proposed \u201censemble strategy model\u201d was 86.51% with a standard deviation of 0.006, and it was robust. In addition, the experimental results of the test dataset revealed that the accuracy, sensitivity, and specificity of the proposed method were 87.54%, 89.25%, and 85.19%, respectively. The accuracy of the five algorithms ranged from 81 to 86%, the sensitivity from 81 to 92%, and the specificity from 77 to 88%. Thus, the experimental results suggest that the model proposed in this study has high accuracy, high sensitivity, and high specificity.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>The \u201censemble strategy model\u201d can be used as a reference for the determination of vancomycin doses in clinical treatment.<\/jats:p><\/jats:sec>","DOI":"10.1186\/s12859-022-05117-8","type":"journal-article","created":{"date-parts":[[2023,3,22]],"date-time":"2023-03-22T15:19:41Z","timestamp":1679498381000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Prediction of vancomycin initial dosage using artificial intelligence models applying ensemble strategy"],"prefix":"10.1186","volume":"22","author":[{"given":"Wen-Hsien","family":"Ho","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tian-Hsiang","family":"Huang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yenming J.","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lang-Yin","family":"Zeng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fen-Fen","family":"Liao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2475-3635","authenticated-orcid":false,"given":"Yeong-Cheng","family":"Liou","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2023,3,22]]},"reference":[{"key":"5117_CR1","unstructured":"Howell L, editor. World Economic Forum. Global risks 2013. 8th edition: an initiative of the Risk Response Network; 2013."},{"key":"5117_CR2","unstructured":"WHO. 2021 Antimicrobial resistance global report on surveillance: 2014 summary. https:\/\/www.who.int\/publications\/i\/item\/WHO-HSE-PED-AIP-2014.2. Accessed 25-Aug-2021."},{"key":"5117_CR3","unstructured":"BBC. 2021. Superbugs to kill 'more than cancer' by 2050. https:\/\/www.bbc.com\/news\/health-30416844. Accessed 25 Aug 2021."},{"key":"5117_CR4","doi-asserted-by":"publisher","first-page":"1226","DOI":"10.1016\/j.dss.2006.02.003","volume":"43","author":"PJ Hu","year":"2007","unstructured":"Hu PJ, Wei CP, Cheng TH, Chen JX. Predicting adequacy of vancomycin regimens: a learning-based classification approach to improving clinical decision making. Decis Support Syst. 2007;43:1226\u201341.","journal-title":"Decis Support Syst"},{"key":"5117_CR5","doi-asserted-by":"publisher","first-page":"1865","DOI":"10.1016\/j.freeradbiomed.2012.02.038","volume":"5","author":"Y Arimura","year":"2012","unstructured":"Arimura Y, Yano T, Hirano M, Sakamoto Y, Egashira N, Oishi R. Mitochondrial superoxide production contributes to vancomycin-induced renal tubular cell apoptosis. Free Radic Biol Med. 2012;5:1865\u201373.","journal-title":"Free Radic Biol Med"},{"key":"5117_CR6","doi-asserted-by":"publisher","first-page":"201","DOI":"10.1111\/j.1365-2125.2010.03679.x","volume":"70","author":"N Revilla","year":"2010","unstructured":"Revilla N, Mart\u00edn-Su\u00e1rez A, P\u00e9rez MP, Gonz\u00e1lez FM, de Gatta MDF. Vancomycin dosing assessment in intensive care unit patients based on a population pharmacokinetic\/pharmacodynamic simulation. Br J Clin Pharmacol. 2010;70:201\u201312.","journal-title":"Br J Clin Pharmacol"},{"key":"5117_CR7","doi-asserted-by":"publisher","first-page":"1361","DOI":"10.1093\/cid\/ciaa303","volume":"71","author":"MJ Rybak","year":"2020","unstructured":"Rybak MJ, Le J, Lodise TP, Levine DP, Bradley JS, Liu C, Mueller BA, Pai MP, Wong-Beringer A, Rotschafer JC, Rodvold KA. Therapeutic monitoring of vancomycin for serious methicillin-resistant Staphylococcus aureus infections: a revised consensus guideline and review by the American Society of Health-System Pharmacists, the Infectious Diseases Society of America, the Pediatric Infectious Diseases Society, and the Society of Infectious Diseases Pharmacists. Clin Infec Dis. 2020;71:1361\u20134.","journal-title":"Clin Infec Dis"},{"key":"5117_CR8","doi-asserted-by":"publisher","first-page":"343","DOI":"10.7326\/0003-4819-94-3-343","volume":"94","author":"RC Moellering","year":"1981","unstructured":"Moellering RC, Krogstad DJ, Greenblatt DJ. Vancomycin therapy in patients with impaired renal function: a nomogram for dosage. Ann Intern Med. 1981;94:343\u20136.","journal-title":"Ann Intern Med"},{"key":"5117_CR9","volume-title":"Basic clinical pharmacokinetics","author":"ME Winter","year":"2003","unstructured":"Winter ME. Basic clinical pharmacokinetics. Philadelphia: Lippincott Williams and Wilkins; 2003."},{"key":"5117_CR10","first-page":"640","volume":"30","author":"G Xu","year":"2018","unstructured":"Xu G, Chen E, Mao E, Che Z, He J. Research of optimal dosing regimens and therapeutic drug monitoring for vancomycin by clinical pharmacists: analysis of 7-year data. Zhonghua Wei Zhong Bing Ji Jiu Yi Xue. 2018;30:640\u20135.","journal-title":"Zhonghua Wei Zhong Bing Ji Jiu Yi Xue"},{"key":"5117_CR11","doi-asserted-by":"publisher","first-page":"757","DOI":"10.1345\/aph.1P634","volume":"45","author":"MO Nunn","year":"2011","unstructured":"Nunn MO, Corallo CE, Aubron C, Poole S, Dooley MJ, Cheng AC. Vancomycin dosing: assessment of time to therapeutic concentration and predictive accuracy of pharmacokinetic modeling software. Ann Pharmacother. 2011;45:757\u201363.","journal-title":"Ann Pharmacother"},{"key":"5117_CR12","doi-asserted-by":"publisher","first-page":"e804","DOI":"10.1016\/j.ijid.2012.07.005","volume":"16","author":"WJ Leu","year":"2012","unstructured":"Leu WJ, Liu YC, Wang HW, Chien HY, Liu HP, Lin YM. Evaluation of a vancomycin dosing nomogram in achieving high target trough concentrations in Taiwanese patients. Int J Infect Dis. 2012;16:e804\u201310.","journal-title":"Int J Infect Dis"},{"key":"5117_CR13","doi-asserted-by":"publisher","first-page":"197","DOI":"10.1007\/BF00116037","volume":"5","author":"RE Schapire","year":"1990","unstructured":"Schapire RE. The strength of weak learnability. Mach Learn. 1990;5:197\u2013227.","journal-title":"Mach Learn"},{"key":"5117_CR14","doi-asserted-by":"publisher","first-page":"13050","DOI":"10.1016\/j.eswa.2011.04.109","volume":"38","author":"WH Ho","year":"2011","unstructured":"Ho WH, Chen JX, Lee IN, Su HC. An ANFIS-based model for predicting adequacy of vancomycin regimen using improved genetic algorithm. Expert Syst Appl. 2011;38:13050\u20136.","journal-title":"Expert Syst Appl"},{"key":"5117_CR15","unstructured":"Freund Y, Schapire RE. Experiments with a new boosting algorithm. In: 13th international conference; 1996. pp. 148\u2013156."},{"key":"5117_CR16","doi-asserted-by":"publisher","first-page":"1","DOI":"10.18637\/jss.v054.i02","volume":"54","author":"E Alfaro","year":"2013","unstructured":"Alfaro E, Gamez M, Garcia N. adabag: an R package for classification with boosting and bagging. J Stat Softw. 2013;54:1\u201335.","journal-title":"J Stat Softw"},{"key":"5117_CR17","volume-title":"Detection estimation and modulation theory, part I: detection, estimation, and filtering theory","author":"HL Van Trees","year":"2013","unstructured":"Van Trees HL. Detection estimation and modulation theory, part I: detection, estimation, and filtering theory. 2nd ed. Hoboken: Wiley; 2013.","edition":"2"},{"key":"5117_CR18","doi-asserted-by":"publisher","first-page":"255","DOI":"10.1023\/B:MACH.0000015881.36452.6e","volume":"5","author":"S D\u017eeroski","year":"2004","unstructured":"D\u017eeroski S, \u017denko B. Is combining classifiers with stacking better than selecting the best one? Mach Learn. 2004;5:255\u201373.","journal-title":"Mach Learn"},{"key":"5117_CR19","doi-asserted-by":"crossref","unstructured":"Zenko B, Todorovski L, Dzeroski S. A comparison of stacking with meta decision trees to bagging, boosting, and stacking with other methods. In: Proceedings 2001 IEEE international conference on data mining 2001; vol. 29, pp. 669\u2013670. IEEE.","DOI":"10.1109\/ICDM.2001.989601"},{"key":"5117_CR20","doi-asserted-by":"publisher","first-page":"561","DOI":"10.1093\/clinchem\/39.4.561","volume":"39","author":"MH Zweig","year":"1993","unstructured":"Zweig MH, Campbell G. Receiver-operating characteristic (ROC) plots: a fundamental evaluation tool in clinical medicine. Clin Chem. 1993;39:561\u201377.","journal-title":"Clin Chem"},{"key":"5117_CR21","doi-asserted-by":"crossref","unstructured":"Spackman KA. Signal detection theory: valuable tools for evaluating inductive learning. In: Proceedings of the sixth international workshop on machine learning; 1989. pp.160\u2013163. Morgan Kaufmann.","DOI":"10.1016\/B978-1-55860-036-2.50047-3"},{"key":"5117_CR22","doi-asserted-by":"publisher","first-page":"29","DOI":"10.1148\/radiology.143.1.7063747","volume":"143","author":"JA Hanley","year":"1982","unstructured":"Hanley JA, McNeil BJ. The meaning and use of the area under a receiver operating characteristic (ROC) curve. Radiology. 1982;143:29\u201336.","journal-title":"Radiology"},{"key":"5117_CR23","unstructured":"Brownlee J. 2018. Machine Learning Mastery. https:\/\/machinelearningmastery.com\/roc-curves-and-precision-recall-curves-for-classification-in-python. Accessed 25 Aug 2021."},{"key":"5117_CR24","unstructured":"Clare L. 2020. KDnuggets. https:\/\/www.kdnuggets.com\/2020\/04\/data-transformation-standardization-normalization.html. Accessed 25 Aug 2021."}],"container-title":["BMC Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12859-022-05117-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s12859-022-05117-8\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12859-022-05117-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,16]],"date-time":"2024-10-16T21:20:02Z","timestamp":1729113602000},"score":1,"resource":{"primary":{"URL":"https:\/\/bmcbioinformatics.biomedcentral.com\/articles\/10.1186\/s12859-022-05117-8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,3,22]]},"references-count":24,"journal-issue":{"issue":"S5","published-online":{"date-parts":[[2021,11]]}},"alternative-id":["5117"],"URL":"https:\/\/doi.org\/10.1186\/s12859-022-05117-8","relation":{},"ISSN":["1471-2105"],"issn-type":[{"value":"1471-2105","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,3,22]]},"assertion":[{"value":"27 November 2022","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"17 December 2022","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"22 March 2023","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"Not applicable.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"Not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"The authors declare that they have no competing interests.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"637"}}