Machine learning models classifiers enable a strong prediction of radioembolization-induced liver disease, and define a new bilirubin threshold for selection of patients.

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Title: Machine learning models classifiers enable a strong prediction of radioembolization-induced liver disease, and define a new bilirubin threshold for selection of patients.
Authors: Rivera I; Univ. Rennes, CLCC Eugène Marquis, INSERM, LTSI - UMR 1099, Rennes, F-35000, France., Bourien H; Department of Oncology, CLCC Eugène Marquis, Rennes, 35033, France., Morel-Corlu E; Univ. Rennes, CLCC Eugène Marquis, INSERM, LTSI - UMR 1099, Rennes, F-35000, France., Peinoit A; Department of Oncology, CLCC Eugène Marquis, Rennes, 35033, France., Le Sourd S; Department of Oncology, CLCC Eugène Marquis, Rennes, 35033, France., Rolland Y; Univ. Rennes, CLCC Eugène Marquis, INSERM, LTSI - UMR 1099, Rennes, F-35000, France., Garin E; Department of Nuclear Medicine, CLCC Eugène Marquis, Rennes, 35033, France., Acosta O; Univ. Rennes, CLCC Eugène Marquis, INSERM, LTSI - UMR 1099, Rennes, F-35000, France., Edeline J; Department of Oncology, CLCC Eugène Marquis, Rennes, 35033, France. j.edeline@rennes.unicancer.fr.
Source: European journal of nuclear medicine and molecular imaging [Eur J Nucl Med Mol Imaging] 2026 May; Vol. 53 (6), pp. 3915-3924. Date of Electronic Publication: 2026 Feb 17.
Publication Type: Journal Article
Journal Info: Publisher: Springer-Verlag Berlin Country of Publication: Germany NLM ID: 101140988 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1619-7089 (Electronic) Linking ISSN: 16197070 NLM ISO Abbreviation: Eur J Nucl Med Mol Imaging Subsets: MEDLINE
Database: MEDLINE Ultimate
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  Data: Machine learning models classifiers enable a strong prediction of radioembolization-induced liver disease, and define a new bilirubin threshold for selection of patients.
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  Data: <searchLink fieldCode="AU" term="%22Rivera+I%22">Rivera I</searchLink>; Univ. Rennes, CLCC Eugène Marquis, INSERM, LTSI - UMR 1099, Rennes, F-35000, France.<br /><searchLink fieldCode="AU" term="%22Bourien+H%22">Bourien H</searchLink>; Department of Oncology, CLCC Eugène Marquis, Rennes, 35033, France.<br /><searchLink fieldCode="AU" term="%22Morel-Corlu+E%22">Morel-Corlu E</searchLink>; Univ. Rennes, CLCC Eugène Marquis, INSERM, LTSI - UMR 1099, Rennes, F-35000, France.<br /><searchLink fieldCode="AU" term="%22Peinoit+A%22">Peinoit A</searchLink>; Department of Oncology, CLCC Eugène Marquis, Rennes, 35033, France.<br /><searchLink fieldCode="AU" term="%22Le+Sourd+S%22">Le Sourd S</searchLink>; Department of Oncology, CLCC Eugène Marquis, Rennes, 35033, France.<br /><searchLink fieldCode="AU" term="%22Rolland+Y%22">Rolland Y</searchLink>; Univ. Rennes, CLCC Eugène Marquis, INSERM, LTSI - UMR 1099, Rennes, F-35000, France.<br /><searchLink fieldCode="AU" term="%22Garin+E%22">Garin E</searchLink>; Department of Nuclear Medicine, CLCC Eugène Marquis, Rennes, 35033, France.<br /><searchLink fieldCode="AU" term="%22Acosta+O%22">Acosta O</searchLink>; Univ. Rennes, CLCC Eugène Marquis, INSERM, LTSI - UMR 1099, Rennes, F-35000, France.<br /><searchLink fieldCode="AU" term="%22Edeline+J%22">Edeline J</searchLink>; Department of Oncology, CLCC Eugène Marquis, Rennes, 35033, France. j.edeline@rennes.unicancer.fr.
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  Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22Springer-Verlag+Berlin%22">Springer-Verlag Berlin </searchLink><i>Country of Publication: </i>Germany <i>NLM ID: </i>101140988 <i>Publication Model: </i>Print-Electronic <i>Cited Medium: </i>Internet <i>ISSN: </i>1619-7089 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2216197070%22">16197070 </searchLink><i>NLM ISO Abbreviation: </i>Eur J Nucl Med Mol Imaging <i>Subsets: </i>MEDLINE
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        Value: 10.1007/s00259-026-07803-8
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        Text: English
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        StartPage: 3915
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      – TitleFull: Machine learning models classifiers enable a strong prediction of radioembolization-induced liver disease, and define a new bilirubin threshold for selection of patients.
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              Text: 2026 May
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