{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,17]],"date-time":"2026-10-17T05:29:02Z","timestamp":1792214942493,"version":"4.4.0"},"reference-count":36,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T00:00:00Z","timestamp":1777593600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T00:00:00Z","timestamp":1777593600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,3,5]],"date-time":"2026-03-05T00:00:00Z","timestamp":1772668800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001691","name":"Japan Society for the Promotion of Science","doi-asserted-by":"publisher","award":["21K17321"],"award-info":[{"award-number":["21K17321"]}],"id":[{"id":"10.13039\/501100001691","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001691","name":"Japan Society for the Promotion of Science","doi-asserted-by":"publisher","award":["23K01288"],"award-info":[{"award-number":["23K01288"]}],"id":[{"id":"10.13039\/501100001691","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001691","name":"Japan Society for the Promotion of Science","doi-asserted-by":"publisher","award":["24K13477"],"award-info":[{"award-number":["24K13477"]}],"id":[{"id":"10.13039\/501100001691","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["clinicalkey.com","clinicalkey.com.au","clinicalkey.es","clinicalkey.fr","clinicalkey.jp","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Travel Medicine and Infectious Disease"],"published-print":{"date-parts":[[2026,5]]},"DOI":"10.1016\/j.tmaid.2026.102966","type":"journal-article","created":{"date-parts":[[2026,3,7]],"date-time":"2026-03-07T03:01:15Z","timestamp":1772852475000},"page":"102966","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":1,"special_numbering":"C","title":["Development of machine-learning models to diagnose influenza among international travellers based on symptoms and epidemiological information"],"prefix":"10.1016","volume":"71","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2979-3449","authenticated-orcid":false,"given":"Yusuke","family":"Asai","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kei","family":"Yamamoto","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hidetoshi","family":"Nomoto","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hidenori","family":"Nakagawa","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Toshinori","family":"Sahara","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Masaya","family":"Yamato","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Naoya","family":"Sakamoto","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ryota","family":"Hase","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Koh","family":"Shinohara","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yukihiro","family":"Yoshimura","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Atsushi","family":"Nagasaka","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Takahiro","family":"Ichikawa","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Natsuko","family":"Imakita","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hiroshi","family":"Miyawaki","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kyoko","family":"Yokota","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yoshihiro","family":"Yamamoto","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Naoya","family":"Itoh","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nobumasa","family":"Okumura","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yusuke","family":"Yoshimi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Norio","family":"Ohmagari","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"issue":"11","key":"10.1016\/j.tmaid.2026.102966_bib1","doi-asserted-by":"crossref","first-page":"2314","DOI":"10.1016\/j.mayocp.2019.02.025","article-title":"Vaccines for international travel","volume":"94","author":"Freedman","year":"2019","journal-title":"Mayo Clin Proc"},{"key":"10.1016\/j.tmaid.2026.102966_bib2","unstructured":"CDC. Post-travel evaluation of the ill traveler. [cited Aug 23 2025] Available from: https:\/\/www.cdc.gov\/yellow-book\/hcp\/post-travel-evaluation\/post-travel-evaluation-of-the-ill-traveler.html."},{"key":"10.1016\/j.tmaid.2026.102966_bib3","doi-asserted-by":"crossref","first-page":"372","DOI":"10.35772\/ghm.2023.01079","article-title":"Epidemiological trends of traveler's diarrhea in Japan: an analysis of imported infectious disease registry data from 2017-2022","volume":"5","author":"Maruki","year":"2023","journal-title":"Glob Health Med"},{"issue":"Suppl 4","key":"10.1016\/j.tmaid.2026.102966_bib4","doi-asserted-by":"crossref","first-page":"S380","DOI":"10.1093\/infdis\/jiw376","article-title":"Infectious disease surveillance in the big data era: towards faster and locally relevant systems","volume":"214","author":"Simonsen","year":"2016","journal-title":"J Infect Dis"},{"issue":"Suppl 4","key":"10.1016\/j.tmaid.2026.102966_bib5","doi-asserted-by":"crossref","first-page":"S375","DOI":"10.1093\/infdis\/jiw400","article-title":"Big data for infectious disease surveillance and modeling","volume":"214","author":"Bansal","year":"2016","journal-title":"J Infect Dis"},{"key":"10.1016\/j.tmaid.2026.102966_bib6","doi-asserted-by":"crossref","first-page":"1377","DOI":"10.1038\/s41598-025-31179-8","article-title":"Intra-scale interaction and cross-scale fusion network for detecting the progression of neurodegeneration in Alzheimer's disease","volume":"16","author":"Babu","year":"2025","journal-title":"Sci Rep"},{"key":"10.1016\/j.tmaid.2026.102966_bib7","doi-asserted-by":"crossref","DOI":"10.1038\/s41598-025-21229-6","article-title":"Privacy preservation in diabetic disease prediction using federated learning based on efficient cross stage recurrent model","volume":"15","author":"Jayalakshmi","year":"2025","journal-title":"Sci Rep"},{"key":"10.1016\/j.tmaid.2026.102966_bib8","series-title":"6th International Conference for Emerging Technology (INCET)","article-title":"Optimising real-time patient data for heart disease prediction using deep neural networks","author":"Anitha","year":"2025"},{"key":"10.1016\/j.tmaid.2026.102966_bib9","doi-asserted-by":"crossref","first-page":"584","DOI":"10.1016\/j.cmi.2019.09.009","article-title":"Machine learning for clinical decision support in infectious diseases: a narrative review of current applications","volume":"26","author":"Peiffer-Smadja","year":"2020","journal-title":"Clin Microbiol Infect"},{"key":"10.1016\/j.tmaid.2026.102966_bib10","doi-asserted-by":"crossref","DOI":"10.1016\/j.heliyon.2024.e28534","article-title":"Machine learning approach to identify malaria risk in travelers using real-world evidence","volume":"10","author":"Fleitas","year":"2024","journal-title":"Heliyon"},{"key":"10.1016\/j.tmaid.2026.102966_bib11","doi-asserted-by":"crossref","DOI":"10.1093\/jtm\/taae054","article-title":"MALrisk: a machine-learning\u2013based tool to predict imported malaria in returned travellers with fever","volume":"31","author":"Balerdi-Sarasola","year":"2024","journal-title":"J Trav Med"},{"key":"10.1016\/j.tmaid.2026.102966_bib12","doi-asserted-by":"crossref","DOI":"10.2196\/31549","article-title":"The development and validation of simplified machine learning algorithms to predict prognosis of hospitalized patients with COVID-19: multicenter, retrospective study","volume":"24","author":"He","year":"2022","journal-title":"J Med Internet Res"},{"key":"10.1016\/j.tmaid.2026.102966_bib13","first-page":"526","article-title":"Predictive model of risk factors of High Flow Nasal Cannula using machine learning in COVID-19","volume":"7","author":"Matsunaga","year":"2022","journal-title":"Infect Dis Model"},{"key":"10.1016\/j.tmaid.2026.102966_bib14","doi-asserted-by":"crossref","first-page":"1728","DOI":"10.1186\/s12889-024-19196-0","article-title":"Machine learning algorithms for predicting COVID-19 mortality in Ethiopia","volume":"24","author":"Alie","year":"2024","journal-title":"BMC Public Health"},{"key":"10.1016\/j.tmaid.2026.102966_bib15","unstructured":"Japan registry for infectious diseases from abroad (J-RIDA). [cited Aug 23 2025] Available from: https:\/\/jrida-jprecor.ncgm.go.jp\/en\/j-rida\/index.html."},{"key":"10.1016\/j.tmaid.2026.102966_bib16","doi-asserted-by":"crossref","first-page":"632","DOI":"10.1016\/j.jiac.2020.11.028","article-title":"Epidemiological trends of imported infectious diseases in Japan: analysis of imported 2-year infectious disease registry data","volume":"27","author":"Kutsuna","year":"2021","journal-title":"J Infect Chemother"},{"key":"10.1016\/j.tmaid.2026.102966_bib17","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pone.0287838","article-title":"Evaluation of potential rabies exposure among Japanese international travelers: a retrospective descriptive study","volume":"18","author":"Nomoto","year":"2023","journal-title":"PLoS One"},{"key":"10.1016\/j.tmaid.2026.102966_bib18","doi-asserted-by":"crossref","first-page":"264","DOI":"10.35772\/ghm.2023.01129","article-title":"Travel-associated sexually transmitted infections in Japan: an observational study using imported infectious disease registry data","volume":"6","author":"Konishi","year":"2024","journal-title":"Glob Health Med"},{"key":"10.1016\/j.tmaid.2026.102966_bib21","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pone.0148506","article-title":"Association between the severity of influenza A(H7N9) virus infections and length of the incubation period","volume":"11","author":"Virlogeux","year":"2016","journal-title":"PLoS One"},{"key":"10.1016\/j.tmaid.2026.102966_bib22","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pone.0153003","article-title":"Influenza seasonality in the tropics and subtropics \u2013 when to vaccinate?","volume":"11","author":"Hirve","year":"2016","journal-title":"PLoS One"},{"key":"10.1016\/j.tmaid.2026.102966_bib24","unstructured":"National Health Service. Respiratory tract infections. [cited Aug 23 2025] Available from: https:\/\/www.nhs.uk\/conditions\/respiratory-tract-infection\/."},{"key":"10.1016\/j.tmaid.2026.102966_bib25","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1186\/s12976-021-00138-x","article-title":"Reconstructing the household transmission of influenza in the suburbs of Tokyo based on clinical cases","volume":"18","author":"Saito","year":"2021","journal-title":"Theor Biol Med Model"},{"issue":"5","key":"10.1016\/j.tmaid.2026.102966_bib27","doi-asserted-by":"crossref","DOI":"10.18637\/jss.v028.i05","article-title":"Building predictive models in R using the caret package","volume":"28","author":"Kuhn","year":"2008","journal-title":"J Stat Software"},{"key":"10.1016\/j.tmaid.2026.102966_bib28","series-title":"Applied predictive modeling","author":"Kuhn","year":"2013"},{"key":"10.1016\/j.tmaid.2026.102966_bib29","series-title":"Modern statistics with R: from wrangling and exploring data to inference and predictive modelling","author":"Thulin","year":"2024"},{"key":"10.1016\/j.tmaid.2026.102966_bib30","doi-asserted-by":"crossref","DOI":"10.1038\/s41598-025-23813-2","article-title":"An intelligent brain tumor detection model using lightweight hybrid twin attentive pyramid convolutional network","volume":"15","author":"Jemina","year":"2025","journal-title":"Sci Rep"},{"key":"10.1016\/j.tmaid.2026.102966_bib31","series-title":"International conference on computing technologies","article-title":"Brain tumor detection using extended optimization based multi-layer perceptron","author":"Jemina","year":"2025"},{"key":"10.1016\/j.tmaid.2026.102966_bib32","doi-asserted-by":"crossref","first-page":"500","DOI":"10.7326\/0003-4819-156-7-201204030-00403","article-title":"Accuracy of rapid influenza diagnostic tests: a meta-analysis","volume":"156","author":"Chartrand","year":"2012","journal-title":"Ann Intern Med"},{"key":"10.1016\/j.tmaid.2026.102966_bib33","doi-asserted-by":"crossref","first-page":"98","DOI":"10.1136\/emermed-2024-214177","article-title":"Multiplex lateral flow test sensitivity and specificity in detecting influenza A, B and SARS-CoV-2 in adult patients in a UK emergency department","volume":"42","author":"Batra","year":"2025","journal-title":"Emerg Med J"},{"key":"10.1016\/j.tmaid.2026.102966_bib34","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pone.0331558","article-title":"A retrospective cohort study evaluating the predictive value of urinary L-FABP combined with the SOFA score for assessing COVID-19 severity","volume":"20","author":"Terakawa","year":"2025","journal-title":"PLoS One"},{"key":"10.1016\/j.tmaid.2026.102966_bib35","doi-asserted-by":"crossref","first-page":"319","DOI":"10.1016\/j.tmaid.2005.10.001","article-title":"Imported dengue fever in Austria 1990-2005","volume":"4","author":"Laferl","year":"2006","journal-title":"Trav Med Infect Dis"},{"key":"10.1016\/j.tmaid.2026.102966_bib36","doi-asserted-by":"crossref","first-page":"70","DOI":"10.1016\/j.ejim.2011.07.003","article-title":"How to save costs by reducing unnecessary testing: lean thinking in clinical practice","volume":"23","author":"Vegting","year":"2012","journal-title":"Eur J Intern Med"},{"key":"10.1016\/j.tmaid.2026.102966_bib37","doi-asserted-by":"crossref","DOI":"10.1016\/j.ijmedinf.2020.104269","article-title":"A systematic literature review on unnecessary diagnostic testing: the role of ICT use","volume":"143","author":"Bai","year":"2020","journal-title":"Int J Med Inf"},{"key":"10.1016\/j.tmaid.2026.102966_bib38","doi-asserted-by":"crossref","DOI":"10.7189\/jogh.12.05047","article-title":"Social contact patterns in Japan in the COVID-19 pandemic during and after the Tokyo Olympic Games","volume":"12","author":"Tsuzuki","year":"2022","journal-title":"J Glob Health"},{"issue":"12","key":"10.1016\/j.tmaid.2026.102966_bib39","doi-asserted-by":"crossref","DOI":"10.2196\/38751","article-title":"Examining the use of an artificial intelligence model to diagnose influenza: development and validation study","volume":"24","author":"Okiyama","year":"2022","journal-title":"J Med Internet Res"},{"issue":"6","key":"10.1016\/j.tmaid.2026.102966_bib41","doi-asserted-by":"crossref","DOI":"10.1093\/jtm\/tax064","article-title":"Redefining priorities towards graded travel-related infectious disease research","volume":"24","author":"Torresi","year":"2017","journal-title":"J Trav Med"}],"container-title":["Travel Medicine and Infectious Disease"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1477893926000165?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1477893926000165?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,7,14]],"date-time":"2026-07-14T13:12:08Z","timestamp":1784034728000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1477893926000165"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,5]]},"references-count":36,"alternative-id":["S1477893926000165"],"URL":"https:\/\/doi.org\/10.1016\/j.tmaid.2026.102966","relation":{},"ISSN":["1477-8939"],"issn-type":[{"value":"1477-8939","type":"print"}],"subject":[],"published":{"date-parts":[[2026,5]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Development of machine-learning models to diagnose influenza among international travellers based on symptoms and epidemiological information","name":"articletitle","label":"Article Title"},{"value":"Travel Medicine and Infectious Disease","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.tmaid.2026.102966","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 The Authors. Published by Elsevier Ltd.","name":"copyright","label":"Copyright"}],"article-number":"102966"}}