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Follow-up of liver metastases: a comparison of deep learning and RECIST 1.1.

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Title: Follow-up of liver metastases: a comparison of deep learning and RECIST 1.1.
Authors: Joskowicz L; School of Computer Science and Engineering, The Hebrew University of Jerusalem, Jerusalem, Israel., Szeskin A; School of Computer Science and Engineering, The Hebrew University of Jerusalem, Jerusalem, Israel., Rochman S; School of Computer Science and Engineering, The Hebrew University of Jerusalem, Jerusalem, Israel., Dodi A; School of Computer Science and Engineering, The Hebrew University of Jerusalem, Jerusalem, Israel., Lederman R; Dept of Radiology, Hadassah Medical Center, Faculty of Medicine, The Hebrew University of Jerusalem, POB 12000, 91120, Jerusalem, Israel., Fruchtman-Brot H; Dept of Radiology, Hadassah Medical Center, Faculty of Medicine, The Hebrew University of Jerusalem, POB 12000, 91120, Jerusalem, Israel., Azraq Y; Dept of Radiology, Hadassah Medical Center, Faculty of Medicine, The Hebrew University of Jerusalem, POB 12000, 91120, Jerusalem, Israel., Sosna J; Dept of Radiology, Hadassah Medical Center, Faculty of Medicine, The Hebrew University of Jerusalem, POB 12000, 91120, Jerusalem, Israel. jacobs@hadassah.org.il.
Source: European radiology [Eur Radiol] 2023 Dec; Vol. 33 (12), pp. 9320-9327. Date of Electronic Publication: 2023 Jul 22.
Publication Type: Journal Article
Journal Info: Publisher: Springer International Country of Publication: Germany NLM ID: 9114774 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1432-1084 (Electronic) Linking ISSN: 09387994 NLM ISO Abbreviation: Eur Radiol Subsets: MEDLINE
Database: MEDLINE Ultimate
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  Data: Follow-up of liver metastases: a comparison of deep learning and RECIST 1.1.
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  Data: <searchLink fieldCode="AU" term="%22Joskowicz+L%22">Joskowicz L</searchLink>; School of Computer Science and Engineering, The Hebrew University of Jerusalem, Jerusalem, Israel.<br /><searchLink fieldCode="AU" term="%22Szeskin+A%22">Szeskin A</searchLink>; School of Computer Science and Engineering, The Hebrew University of Jerusalem, Jerusalem, Israel.<br /><searchLink fieldCode="AU" term="%22Rochman+S%22">Rochman S</searchLink>; School of Computer Science and Engineering, The Hebrew University of Jerusalem, Jerusalem, Israel.<br /><searchLink fieldCode="AU" term="%22Dodi+A%22">Dodi A</searchLink>; School of Computer Science and Engineering, The Hebrew University of Jerusalem, Jerusalem, Israel.<br /><searchLink fieldCode="AU" term="%22Lederman+R%22">Lederman R</searchLink>; Dept of Radiology, Hadassah Medical Center, Faculty of Medicine, The Hebrew University of Jerusalem, POB 12000, 91120, Jerusalem, Israel.<br /><searchLink fieldCode="AU" term="%22Fruchtman-Brot+H%22">Fruchtman-Brot H</searchLink>; Dept of Radiology, Hadassah Medical Center, Faculty of Medicine, The Hebrew University of Jerusalem, POB 12000, 91120, Jerusalem, Israel.<br /><searchLink fieldCode="AU" term="%22Azraq+Y%22">Azraq Y</searchLink>; Dept of Radiology, Hadassah Medical Center, Faculty of Medicine, The Hebrew University of Jerusalem, POB 12000, 91120, Jerusalem, Israel.<br /><searchLink fieldCode="AU" term="%22Sosna+J%22">Sosna J</searchLink>; Dept of Radiology, Hadassah Medical Center, Faculty of Medicine, The Hebrew University of Jerusalem, POB 12000, 91120, Jerusalem, Israel. jacobs@hadassah.org.il.
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  Data: <searchLink fieldCode="JN" term="%229114774%22">European radiology</searchLink> [Eur Radiol] 2023 Dec; Vol. 33 (12), pp. 9320-9327. <i>Date of Electronic Publication: </i>2023 Jul 22.
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  Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22Springer+International%22">Springer International </searchLink><i>Country of Publication: </i>Germany <i>NLM ID: </i>9114774 <i>Publication Model: </i>Print-Electronic <i>Cited Medium: </i>Internet <i>ISSN: </i>1432-1084 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2209387994%22">09387994 </searchLink><i>NLM ISO Abbreviation: </i>Eur Radiol <i>Subsets: </i>MEDLINE
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        Value: 10.1007/s00330-023-09926-0
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      – TitleFull: Follow-up of liver metastases: a comparison of deep learning and RECIST 1.1.
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              M: 12
              Text: 2023 Dec
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