The probing of biological systems with various omics technologies at an exceptional scale has generated huge heterogeneous data-sets that create hurdles for data analysis. This has encouraged the researchers to use various computational approaches such as data mining, deep learning, machine learning and statistical methods to analyze the data-sets. Moreover this has ushered the development of novel data integration methodologies, for instance radiomics is a very recent addition to the omics field wherein data-characterization algorithms are being used to extract information from radiographic medical images.
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