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Med. Biol."],"published-print":{"date-parts":[[2026,2,14]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>The high-throughput extraction of radiomics features from medical images for predictive modelling holds great promise to improve the clinical management of patients. Previous meta-analyses into the radiomics quality score (RQS) applied in the literature have shown that after more than a decade of investigation, issues with workflow standardisation, model reproducibility, validation, and data accessibility persist and impede the clinical translation of radiomics-based models. These systematic findings have informed a timely review of the best practices and pitfalls to avoid within radiomics and predictive modelling, with a focus on realistic radiomics modelling in the context of limited sample sizes. Each section covers a radiomics topic that encompasses one or more RQS criteria and is broken into subsections as follows: (1) a discussion of the background and recommendations on the respective topic, (2) key findings from our meta-analyses and discovered pitfalls, and (3) a succinct list of actionable items that reflect best practice. New and emerging quality appraisal tools and the future direction of radiomics are also discussed.<\/jats:p>","DOI":"10.1088\/1361-6560\/ae36e0","type":"journal-article","created":{"date-parts":[[2026,1,12]],"date-time":"2026-01-12T22:51:33Z","timestamp":1768258293000},"page":"03TR02","update-policy":"https:\/\/doi.org\/10.1088\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["The long and winding road of radiomics: learnings from two meta-analyses of the radiomics quality score"],"prefix":"10.1088","volume":"71","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9009-5909","authenticated-orcid":true,"given":"Nathaniel","family":"Barry","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6524-539X","authenticated-orcid":false,"given":"Jake","family":"Kendrick","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-8445-051X","authenticated-orcid":true,"given":"Kaylee","family":"Molin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-0007-9401","authenticated-orcid":true,"given":"Suning","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8306-7742","authenticated-orcid":true,"given":"Pejman","family":"Rowshanfarzad","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6636-8807","authenticated-orcid":false,"given":"Ghulam Mubashar","family":"Hassan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9349-2275","authenticated-orcid":true,"given":"Jason","family":"Dowling","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5101-6107","authenticated-orcid":true,"given":"Jeremy S L","family":"Ong","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0221-2854","authenticated-orcid":false,"given":"Paul M","family":"Parizel","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8622-159X","authenticated-orcid":false,"given":"Michael S","family":"Hofman","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7307-396X","authenticated-orcid":true,"given":"Burak","family":"Kocak","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1452-1574","authenticated-orcid":true,"given":"Renato","family":"Cuocolo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6875-0719","authenticated-orcid":true,"given":"Martin A","family":"Ebert","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"266","published-online":{"date-parts":[[2026,2,11]]},"reference":[{"key":"pmbae36e0bib1","doi-asserted-by":"publisher","first-page":"132","DOI":"10.1109\/MSP.2019.2900993","type":"journal-article","article-title":"From handcrafted to deep-learning-based cancer radiomics: challenges and opportunities","volume":"36","author":"Afshar","year":"2019","journal-title":"IEEE Signal Process. 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