A pipeline of machine learning-driven multi-modal data fusion methods for prognostic risk analysis in bevacizumab-treated metastatic colorectal cancer.
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| Title: | A pipeline of machine learning-driven multi-modal data fusion methods for prognostic risk analysis in bevacizumab-treated metastatic colorectal cancer. |
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| Authors: | Thomas, Valentina1 (AUTHOR), Nyamundanda, Gift2 (AUTHOR), Lärkeryd, Adrian3 (AUTHOR), Hari, P. S.2,4 (AUTHOR), Miller, Ian S.1 (AUTHOR), Venken, Tom5,6 (AUTHOR), Smeets, Dominiek5,6 (AUTHOR), Boeckx, Bram5,6 (AUTHOR), Betge, Johannes7,8,9 (AUTHOR), Ebert, Matthias P. A.7,9 (AUTHOR), Gaiser, Timo10 (AUTHOR), Murphy, Verena11 (AUTHOR), Kay, Elaine12 (AUTHOR), Verheul, Henk M.13 (AUTHOR), O'Farrell, Alice C.1 (AUTHOR), Cremolini, Chiara14,15 (AUTHOR), Marmorino, Federica14,15 (AUTHOR), Gallagher, William M.16 (AUTHOR), Barat, Ana17 (AUTHOR), Klinger, Rut18 (AUTHOR) |
| Source: | Scientific Reports. 4/13/2026, Vol. 16 Issue 1, p1-10. 10p. |
| Database: | Academic Search Ultimate |
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| ISSN: | 20452322 |
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| DOI: | 10.1038/s41598-026-39189-w |
