{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,9]],"date-time":"2026-10-09T01:43:53Z","timestamp":1791510233855,"version":"4.3.4"},"reference-count":27,"publisher":"Elsevier BV","issue":"17","license":[{"start":{"date-parts":[[2024,9,1]],"date-time":"2024-09-01T00:00:00Z","timestamp":1725148800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2024,9,1]],"date-time":"2024-09-01T00:00:00Z","timestamp":1725148800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2024,8,19]],"date-time":"2024-08-19T00:00:00Z","timestamp":1724025600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"content-domain":{"domain":["cell.com","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Heliyon"],"published-print":{"date-parts":[[2024,9]]},"DOI":"10.1016\/j.heliyon.2024.e36601","type":"journal-article","created":{"date-parts":[[2024,8,23]],"date-time":"2024-08-23T05:48:58Z","timestamp":1724392138000},"page":"e36601","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":5,"title":["Diagnostic performance of MRI-based radiomics models using machine learning approaches for the triple classification of parotid tumors"],"prefix":"10.1016","volume":"10","author":[{"given":"Junjie","family":"Guo","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiajun","family":"Feng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuqian","family":"Huang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xianqing","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4993-2661","authenticated-orcid":false,"given":"Zhenbin","family":"Hu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Quan","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Honggang","family":"Xu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"issue":"3","key":"10.1016\/j.heliyon.2024.e36601_bib1","doi-asserted-by":"crossref","first-page":"170","DOI":"10.5455\/medarh.2022.76.-010.5455\/medarh.2022.76.170-174","article-title":"Retrospective analysis of 136 patients operated for a parotid global tumor","volume":"76","author":"Dedeoglu","year":"2022","journal-title":"Med. Arch."},{"issue":"1","key":"10.1016\/j.heliyon.2024.e36601_bib2","doi-asserted-by":"crossref","DOI":"10.1016\/j.amjoto.2020.102590","article-title":"The role of fine needle aspiration biopsy in deep lobe parotid tumors: comparison of preoperative cytology and postoperative histopathologic results","volume":"42","author":"Seyhun","year":"2021","journal-title":"Am. J. Otolaryngol."},{"issue":"2","key":"10.1016\/j.heliyon.2024.e36601_bib3","doi-asserted-by":"crossref","first-page":"358","DOI":"10.1002\/hed.25503","article-title":"Values of fine-needle aspiration cytology of parotid gland tumors: a review of 996 cases at a single institution","volume":"41","author":"Suzuki","year":"2019","journal-title":"Head Neck"},{"issue":"7","key":"10.1016\/j.heliyon.2024.e36601_bib4","doi-asserted-by":"crossref","first-page":"2275","DOI":"10.21037\/tcr-22-695","article-title":"Multimodal magnetic resonance imaging for the diagnosis of parotid gland malignancies: systematic review and meta-analysis","volume":"11","author":"Li","year":"2022","journal-title":"Transl. Cancer Res."},{"issue":"2","key":"10.1016\/j.heliyon.2024.e36601_bib5","doi-asserted-by":"crossref","first-page":"563","DOI":"10.1148\/radiol.2015151169","article-title":"Radiomics: images are more than pictures, they are data","volume":"278","author":"Gillies","year":"2016","journal-title":"Radiology"},{"key":"10.1016\/j.heliyon.2024.e36601_bib6","doi-asserted-by":"crossref","first-page":"4","DOI":"10.1016\/j.mri.2019.02.013","article-title":"Differentiation of spinal metastases originated from lung and other cancers using radiomics and deep learning based on DCE-MRI","volume":"64","author":"Lang","year":"2019","journal-title":"Magn. Reson. Imag."},{"issue":"7","key":"10.1016\/j.heliyon.2024.e36601_bib7","doi-asserted-by":"crossref","first-page":"1468","DOI":"10.1007\/s00259-019-04313-8","article-title":"PET\/CT radiomics in breast cancer: promising tool for prediction of pathological response to neoadjuvant chemotherapy","volume":"46","author":"Antunovic","year":"2019","journal-title":"Eur. J. Nucl. Med. Mol. Imag."},{"key":"10.1016\/j.heliyon.2024.e36601_bib8","article-title":"An MRI-based radiomics nomogram to assess recurrence risk in sinonasal malignant tumors","author":"Wang","year":"2022","journal-title":"J. Magn. Reson. Imag. : JMRI."},{"issue":"3","key":"10.1016\/j.heliyon.2024.e36601_bib9","doi-asserted-by":"crossref","first-page":"797","DOI":"10.1016\/j.surg.2021.03.049","article-title":"Machine learning for the prediction of pathologic pneumatosis intestinalis","volume":"170","author":"Clancy","year":"2021","journal-title":"Surgery"},{"issue":"6","key":"10.1016\/j.heliyon.2024.e36601_bib10","doi-asserted-by":"crossref","first-page":"472.e411","DOI":"10.1016\/j.crad.2020.10.019","article-title":"A triple-classification radiomics model for the differentiation of pleomorphic adenoma, Warthin tumour, and malignant salivary gland tumours on the basis of diffusion-weighted imaging","volume":"76","author":"Shao","year":"2021","journal-title":"Clin. Radiol."},{"issue":"1128","key":"10.1016\/j.heliyon.2024.e36601_bib11","doi-asserted-by":"crossref","DOI":"10.1259\/bjr.20210340","article-title":"Diagnostic performance of qualitative and radiomics approach to parotid gland tumors: which is the added benefit of texture analysis?","volume":"94","author":"Vernuccio","year":"2021","journal-title":"Br. J. Radiol."},{"issue":"11","key":"10.1016\/j.heliyon.2024.e36601_bib12","doi-asserted-by":"crossref","first-page":"900","DOI":"10.3390\/diagnostics10110900","article-title":"Can magnetic resonance radiomics analysis discriminate parotid gland tumors? A pilot study","volume":"10","author":"Gabelloni","year":"2020","journal-title":"Diagnostics"},{"issue":"1","key":"10.1016\/j.heliyon.2024.e36601_bib13","doi-asserted-by":"crossref","first-page":"191","DOI":"10.1186\/s12880-022-00924-0","article-title":"Magnetic resonance imaging of parotid gland tumors: a pictorial essay","volume":"22","author":"Kim","year":"2022","journal-title":"BMC Med. Imag."},{"issue":"7","key":"10.1016\/j.heliyon.2024.e36601_bib14","doi-asserted-by":"crossref","first-page":"1202","DOI":"10.3174\/ajnr.A2520","article-title":"MR imaging of parotid tumors: typical lesion characteristics in MR imaging improve discrimination between benign and malignant disease","volume":"32","author":"Christe","year":"2011","journal-title":"AJNR American journal of neuroradiology"},{"issue":"1","key":"10.1016\/j.heliyon.2024.e36601_bib15","doi-asserted-by":"crossref","first-page":"257","DOI":"10.3390\/tomography8010020","article-title":"High-resolution 3D versus standard-resolution 2D T2-weighted turbo spin echo MRI for the assessment of lumbar nerve root compromise","volume":"8","author":"Sartoretti","year":"2022","journal-title":"Tomography (Ann Arbor, Mich)"},{"issue":"3","key":"10.1016\/j.heliyon.2024.e36601_bib16","doi-asserted-by":"crossref","first-page":"1116","DOI":"10.1016\/j.neuroimage.2006.01.015","article-title":"User-guided 3D active contour segmentation of anatomical structures: significantly improved efficiency and reliability","volume":"31","author":"Yushkevich","year":"2006","journal-title":"Neuroimage"},{"issue":"11","key":"10.1016\/j.heliyon.2024.e36601_bib17","doi-asserted-by":"crossref","first-page":"6241","DOI":"10.1007\/s00330-020-06957-9","article-title":"Reliability and prognostic value of radiomic features are highly dependent on choice of feature extraction platform","volume":"30","author":"Fornacon-Wood","year":"2020","journal-title":"Eur. Radiol."},{"issue":"24","key":"10.1016\/j.heliyon.2024.e36601_bib18","doi-asserted-by":"crossref","DOI":"10.1088\/1361-6560\/ac3eac","article-title":"Impact of image pre-processing methods on computed tomography radiomics features in chronic obstructive pulmonary disease","volume":"66","author":"Au","year":"2021","journal-title":"Phys. Med. Biol."},{"issue":"10","key":"10.1016\/j.heliyon.2024.e36601_bib19","doi-asserted-by":"crossref","first-page":"4431","DOI":"10.21037\/qims-21-86","article-title":"Radiomics feature reliability assessed by intraclass correlation coefficient: a systematic review","volume":"11","author":"Xue","year":"2021","journal-title":"Quant. Imag. Med. Surg."},{"key":"10.1016\/j.heliyon.2024.e36601_bib20","doi-asserted-by":"crossref","first-page":"9","DOI":"10.1016\/j.clinimag.2021.09.005","article-title":"Parotid Warthin's tumor: novel MR imaging score as diagnostic indicator","volume":"81","author":"Luna","year":"2022","journal-title":"Clin. Imag."},{"key":"10.1016\/j.heliyon.2024.e36601_bib21","first-page":"10","article-title":"[Performance of the magnetic resonance imaging in parotid gland tumor histopathology]","volume":"39","author":"Masmoudi","year":"2021","journal-title":"The Pan African medical journal"},{"key":"10.1016\/j.heliyon.2024.e36601_bib22","doi-asserted-by":"crossref","DOI":"10.3389\/falgy.2022.813927","article-title":"Hypersensitivity to gadolinium-based contrast media","volume":"3","author":"Gracia Bara","year":"2022","journal-title":"Frontiers in allergy"},{"issue":"11","key":"10.1016\/j.heliyon.2024.e36601_bib23","doi-asserted-by":"crossref","first-page":"2228","DOI":"10.1007\/s00259-019-04447-9","article-title":"A multiparametric analysis based on DCE-MRI to improve the accuracy of parotid tumor discrimination","volume":"46","author":"Xu","year":"2019","journal-title":"Eur. J. Nucl. Med. Mol. Imag."},{"issue":"4","key":"10.1016\/j.heliyon.2024.e36601_bib24","doi-asserted-by":"crossref","DOI":"10.1259\/dmfr.20200391","article-title":"Parotid gland tumors: comparison of conventional and diffusion-weighted MRI findings with histopathological results","volume":"50","author":"Karaman","year":"2021","journal-title":"Dentomaxillofacial Radiol."},{"key":"10.1016\/j.heliyon.2024.e36601_bib25","doi-asserted-by":"crossref","first-page":"4006","DOI":"10.1038\/ncomms5006","article-title":"Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach","volume":"5","author":"Aerts","year":"2014","journal-title":"Nat. Commun."},{"issue":"11","key":"10.1016\/j.heliyon.2024.e36601_bib26","doi-asserted-by":"crossref","DOI":"10.1097\/MD.0000000000014876","article-title":"Intratumoral heterogeneity as measured using the tumor-stroma ratio and PET texture analyses in females with lung adenocarcinomas differs from that of males with lung adenocarcinomas or squamous cell carcinomas","volume":"98","author":"Koh","year":"2019","journal-title":"Medicine"},{"issue":"7","key":"10.1016\/j.heliyon.2024.e36601_bib27","doi-asserted-by":"crossref","first-page":"948","DOI":"10.1109\/TIP.2005.849295","article-title":"A steerable complex wavelet construction and its application to image denoising","volume":"14","author":"Bharath","year":"2005","journal-title":"IEEE Trans. Image Process. : a publication of the IEEE Signal Processing Society"}],"container-title":["Heliyon"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S2405844024126321?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S2405844024126321?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,9,27]],"date-time":"2026-09-27T21:13:44Z","timestamp":1790543624000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S2405844024126321"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,9]]},"references-count":27,"journal-issue":{"issue":"17","published-print":{"date-parts":[[2024,9]]}},"alternative-id":["S2405844024126321"],"URL":"https:\/\/doi.org\/10.1016\/j.heliyon.2024.e36601","relation":{},"ISSN":["2405-8440"],"issn-type":[{"value":"2405-8440","type":"print"}],"subject":[],"published":{"date-parts":[[2024,9]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Diagnostic performance of MRI-based radiomics models using machine learning approaches for the triple classification of parotid tumors","name":"articletitle","label":"Article Title"},{"value":"Heliyon","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.heliyon.2024.e36601","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2024 The Authors. Published by Elsevier Ltd.","name":"copyright","label":"Copyright"}],"article-number":"e36601"}}