20.500.12556/RUL-125567 Democratized image analytics by visual programming through integration of deep models and small-scale machine learning Analysis of biomedical images requires computational expertize that are uncommon among biomedical scientists. Deep learning approaches for image analysis provide an opportunity to develop user-friendly tools for exploratory data analysis. Here, we use the visual programming toolbox Orange (http://orange.biolab.si) to simplify image analysis by integrating deep-learning embedding, machine learning procedures, and data visualization. Orange supports the construction of data analysis workflows by assembling components for data preprocessing, visualization, and modeling. We equipped Orange with components that use pre-trained deep convolutional networks to profile images with vectors of features. These vectors are used in image clustering and classification in a framework that enables mining of image sets for both novel and experienced users. We demonstrate the utility of the tool in image analysis of progenitor cells in mouse bone healing, identification of developmental competence in mouse oocytes, subcellular protein localization in yeast, and developmental morphology of social amoebae. algorithm biochemical composition data assimilation data mining image analysis machine learning numerical model protein visualization true false true Angleški jezik Ni določen Članek v reviji 2021-03-25 14:51:40 2021-03-25 14:51:40 2022-09-05 03:51:24 0000-00-00 00:00:00 2019 0 0 7 str. art. 4551 Vol. 10 2019 0000-00-00 Zaloznikova Objavljeno NiDoloceno 0000-00-00 0000-00-00 0000-00-00 004.9:577 2041-1723 10.1038/s41467-019-12397-x 32755751 2315876 RAZ_Godec_Primoz_2019.pdf RAZ_Godec_Primoz_2019.pdf 1 0CE6AC40B49EAF2D9DF5D26C2C702E95 5d882bee6ed7f709463c22fcf213aa98c237953d91fd8f2cd4cadd885747923e bc27fcae-a1bb-11eb-a523-00155dcfd717 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=141329 https://www.nature.com/articles/s41467-019-12397-x 1 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=141330 Fakulteta za računalništvo in informatiko Biotehniška fakulteta 0 0 0