Radiomics and Artificial Intelligence for Biomarker and Prediction Model Development in Oncology
- PMID: 31388413
- PMCID: PMC6667772
- DOI: 10.1016/j.csbj.2019.07.001
Radiomics and Artificial Intelligence for Biomarker and Prediction Model Development in Oncology
Abstract
Unlabelled Image.
Keywords: Artificial intelligence; Biomarker; Machine learning; Precision oncology; Radiomics; Texture analysis.
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References
-
- Therasse P. New guidelines to evaluate the response to treatment in solid tumors. European Organization for Research and Treatment of Cancer, National Cancer Institute of the United States, National Cancer Institute of Canada. J Natl Cancer Inst. 2000;92(3):205–216. - PubMed
-
- Jaffe C.C. Measures of response: RECIST, WHO, and new alternatives. J Clin Oncol. 2006;24(20):3245–3251. - PubMed
-
- Lambin P. Radiomics: the bridge between medical imaging and personalized medicine. Nat Rev Clin Oncol. 2017;14(12):749–762. - PubMed
-
- Lubner M.G. CT texture analysis: definitions, applications, biologic correlates, and challenges. Radiographics. 2017;37(5):1483–1503. - PubMed
-
- Ganeshan B. Texture analysis in non-contrast enhanced CT: impact of malignancy on texture in apparently disease-free areas of the liver. Eur J Radiol. 2009;70(1):101–110. - PubMed
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