{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T22:24:53Z","timestamp":1780352693102,"version":"3.54.1"},"reference-count":37,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"funder":[{"name":"Basic Public Welfare Research Project of Zhejiang Province in 2021","award":["LGF21H110001"],"award-info":[{"award-number":["LGF21H110001"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2021]]},"DOI":"10.1109\/access.2021.3051095","type":"journal-article","created":{"date-parts":[[2021,1,13]],"date-time":"2021-01-13T19:18:10Z","timestamp":1610565490000},"page":"15181-15190","source":"Crossref","is-referenced-by-count":28,"title":["Infrared Thermal Images Classification for Pressure Injury Prevention Incorporating the Convolutional Neural Networks"],"prefix":"10.1109","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1607-5475","authenticated-orcid":false,"given":"Yu","family":"Wang","sequence":"first","affiliation":[{"name":"The First Affiliated Hospital, Wenzhou Medical University, Wenzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaoqiong","family":"Jiang","sequence":"additional","affiliation":[{"name":"College of Nursing, Wenzhou Medical University, Wenzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kangyuan","family":"Yu","sequence":"additional","affiliation":[{"name":"College of Optometry and Biomedical Engineering, Wenzhou Medical University, Wenzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4245-5727","authenticated-orcid":false,"given":"Fuqian","family":"Shi","sequence":"additional","affiliation":[{"name":"Rutgers Cancer Institute of New Jersey, New Brunswick, NJ, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Longjiang","family":"Qin","sequence":"additional","affiliation":[{"name":"The First Affiliated Hospital, Wenzhou Medical University, Wenzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hui","family":"Zhou","sequence":"additional","affiliation":[{"name":"The First Affiliated Hospital, Wenzhou Medical University, Wenzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fuman","family":"Cai","sequence":"additional","affiliation":[{"name":"College of Nursing, Wenzhou Medical University, Wenzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1016\/j.infrared.2017.09.005"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1111\/jan.13414"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1016\/j.jvs.2011.03.287"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1007\/s11042-018-6974-5"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.4028\/www.scientific.net\/AMM.401-403.1519"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/5.726791"},{"key":"ref35","doi-asserted-by":"crossref","first-page":"26","DOI":"10.1097\/WON.0000000000000388","article-title":"Artificial neural network: A method for prediction of surgery-related pressure injury in cardiovascular surgical patients","volume":"45","author":"chen","year":"2018","journal-title":"Journal of Wound Ostomy and Continence Nursing Official Publication of the Wound Ostomy and Continence Nurses Society\/WOCN"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1049\/joe.2016.0060"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1007\/s10916-018-1088-1"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/IEMBS.2004.1403370"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.3004056"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1080\/21681163.2020.1824685"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1007\/s11517-018-1835-y"},{"key":"ref15","first-page":"67","article-title":"CNN intelligent early warning for apple skin lesion image acquired by infrared video sensors","volume":"22","author":"tan","year":"2016","journal-title":"High Technol Lett"},{"key":"ref16","first-page":"1279","article-title":"Significance of softmax-based features in comparison to distance metric learning-based features","volume":"42","author":"horiguchi","year":"2020","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"ref17","first-page":"1097","article-title":"ImageNet classification with deep convolutional neural networks","author":"krizhevsky","year":"2012","journal-title":"Proc 25th Int Conf Neural Inf Process Syst"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1088\/1757-899X\/331\/1\/012019"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1016\/0167-8655(85)90004-2"},{"key":"ref28","first-page":"122","article-title":"Modified CNN algorithm based on Dropout and ADAM optimizer","volume":"46","author":"yang","year":"2018","journal-title":"J Huazhong Univ Sci Technol"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1111\/iwj.12604"},{"key":"ref27","doi-asserted-by":"crossref","first-page":"1028","DOI":"10.1111\/jocn.14091","article-title":"Incidence and risk factors associated with the development of pressure ulcers in an intensive care unit","volume":"27","author":"gonz\u00e1lez-m\u00e9ndez","year":"2017","journal-title":"J Clin Nursing"},{"key":"ref3","first-page":"1","article-title":"Predictive validity of the Braden scale, Norton scale, and Waterlow scale in the Czech Republic","volume":"23","author":"\u0161atekov\u00e1","year":"2016","journal-title":"Int J Nurs Pract"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1016\/j.jtv.2020.08.001"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1145\/1961189.1961199"},{"key":"ref5","first-page":"1","article-title":"Application of infrared thermography in diagnosing peripherally inserted central venous catheter infections in children with cancer","volume":"40","author":"casanova","year":"2019","journal-title":"Physiolog Meas"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1097\/WON.0000000000000392"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/EMBC.2017.8037110"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1097\/WON.0000000000000292"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1142\/S0219519410003459"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jccw.2016.07.001"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2018.10.006"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2018.2841987"},{"key":"ref21","first-page":"1889","article-title":"Working set selection using second order information for training support vector machines","volume":"6","author":"fan","year":"2005","journal-title":"J Mach Learn Res"},{"key":"ref24","first-page":"974","article-title":"Machine learning techniques on multidimensional curve fitting data based on R-square and chi-square methods","volume":"6","author":"vidyullatha","year":"2016","journal-title":"International Journal of Computers and Electrical Engineering"},{"key":"ref23","first-page":"1157","article-title":"An introduction to variable and feature selection","volume":"3","author":"guyon","year":"2003","journal-title":"J Mach Learn Res"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.12968\/jowc.2016.25.4.177"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1002\/sim.7008"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/9312710\/09320470.pdf?arnumber=9320470","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,9,8]],"date-time":"2022-09-08T20:14:34Z","timestamp":1662668074000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9320470\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"references-count":37,"URL":"https:\/\/doi.org\/10.1109\/access.2021.3051095","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021]]}}}