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Machine and deep learning methods for radiomics
May 2020 • Michele Avanzo, Lise Wei, Joseph Stancanello, Martin Vallières, Arvind Rao, Olivier Morin, Sarah A. Mattonen, Issam El Naqa
Radiomics is an emerging area in quantitative image analysis that aims to relate large‐scale extracted imaging information to clinical and biological endpoints. The development of quantitative imaging methods along with machine learning has enabled the opportunity to move data science research towards translation for more personalized cancer treatments. Accumulating evidence has indeed demonstrated that noninvasive advanced imaging analytics, that is, radiomics, can reveal key components of tumor phenotype for mul…
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