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A clinical decision support system optimising adjuvant chemotherapy for colorectal cancers by integrating deep learning and pathological staging markers: a development and validation study.
Lancet Oncol. 2022 Sep;23(9):1221-1232. doi: 10.1016/S1470-2045(22)00391-6. Epub 2022 Aug 11.
Lancet Oncol. 2022.
PMID: 35964620
Deep learning for prediction of colorectal cancer outcome: a discovery and validation study.
Skrede OJ, De Raedt S, Kleppe A, Hveem TS, Liestøl K, Maddison J, Askautrud HA, Pradhan M, Nesheim JA, Albregtsen F, Farstad IN, Domingo E, Church DN, Nesbakken A, Shepherd NA, Tomlinson I, Kerr R, Novelli M, Kerr DJ, Danielsen HE.
Skrede OJ, et al.
Lancet. 2020 Feb 1;395(10221):350-360. doi: 10.1016/S0140-6736(19)32998-8.
Lancet. 2020.
PMID: 32007170
Clinical Trial.
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Deep learning and cancer biomarkers: recognising lead-time bias - Authors' reply.
Liestøl K, Kleppe A, Skrede OJ, De Raedt S, Kerr DJ, Danielsen HE.
Liestøl K, et al. Among authors: skrede oj.
Lancet. 2021 Jan 16;397(10270):194-195. doi: 10.1016/S0140-6736(21)00035-0.
Lancet. 2021.
PMID: 33453777
No abstract available.
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Designing deep learning studies in cancer diagnostics.
Kleppe A, Skrede OJ, De Raedt S, Liestøl K, Kerr DJ, Danielsen HE.
Kleppe A, et al. Among authors: skrede oj.
Nat Rev Cancer. 2021 Mar;21(3):199-211. doi: 10.1038/s41568-020-00327-9. Epub 2021 Jan 29.
Nat Rev Cancer. 2021.
PMID: 33514930
Review.
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