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Sixty-two CT texture-based features were extracted from 2D images of the arterial and portal phase CTs. We conducted data compression and feature selections using principal component analysis (PCA) and produced the SVM classifier. Four readers participated in this observer performance study and the statistical significance of differences with and without the SVM was assessed by receiver operating characteristic (ROC) analysis.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Results<\/jats:title>\n                <jats:p>The SVM performance indicated a high performance in differentiating focal-type AIP and PD (AUC\u2009=\u20090.920). The AUC for all 4 readers increased significantly from 0.827 to 0.911 when using the SVM outputs (<jats:italic>p<\/jats:italic>\u2009=\u20090.010). The AUC for inexperienced readers increased significantly from 0.781 to 0.905 when using the SVM outputs (<jats:italic>p<\/jats:italic>\u2009=\u20090.310). The AUC for experienced readers increased from 0.875 to 0.912 when using the SVM outputs, however, there was no significant difference (<jats:italic>p<\/jats:italic>\u2009=\u20090.018).<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Conclusion<\/jats:title>\n                <jats:p>The use of SVM classifier using CT texture-based features improved the diagnostic performance for differentiating focal-type AIP and PD on CT.<\/jats:p>\n              <\/jats:sec>","DOI":"10.1007\/s11604-022-01298-7","type":"journal-article","created":{"date-parts":[[2022,6,21]],"date-time":"2022-06-21T05:03:53Z","timestamp":1655787833000},"page":"1156-1165","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":20,"title":["The effect of CT texture-based analysis using machine learning approaches on radiologists' performance in differentiating focal-type autoimmune pancreatitis and pancreatic duct carcinoma"],"prefix":"10.1007","volume":"40","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9851-1287","authenticated-orcid":false,"given":"Kenta","family":"Anai","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yoshiko","family":"Hayashida","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Issei","family":"Ueda","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Eri","family":"Hozuki","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuuta","family":"Yoshimatsu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jun","family":"Tsukamoto","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Toshihiko","family":"Hamamura","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Norihiro","family":"Onari","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Takatoshi","family":"Aoki","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yukunori","family":"Korogi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2022,6,21]]},"reference":[{"key":"1298_CR1","doi-asserted-by":"publisher","first-page":"2670","DOI":"10.1056\/NEJMra061200","volume":"355","author":"DL Finkelberg","year":"2006","unstructured":"Finkelberg DL, Sahani D, Deshpande V, Brugge WR. 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