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Democratized image analytics by visual programming through integration of deep models and small-scale machine learning
ID Godec, Primož (Author), ID Pančur, Matjaž (Author), ID Ilenič, Nejc (Author), ID Čopar, Andrej (Author), ID Stražar, Martin (Author), ID Erjavec, Aleš (Author), ID Pretnar Žagar, Ajda (Author), ID Demšar, Janez (Author), ID Starič, Anže (Author), ID Toplak, Marko (Author), ID Žagar, Lan (Author), ID Hartman, Jan (Author), ID Hamilton, Wang (Author), ID Bellazzi, Riccardo (Author), ID Petrovič, Uroš (Author), ID Garagna, Silvia (Author), ID Zuccotti, Maurizio (Author), ID Park, Dongsu (Author), ID Shaulsky, Gad (Author), ID Zupan, Blaž (Author)

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Abstract
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.

Language:English
Keywords:algorithm, biochemical composition, data assimilation, data mining, image analysis, machine learning, numerical model, protein, visualization
Work type:Article
Typology:1.01 - Original Scientific Article
Organization:FRI - Faculty of Computer and Information Science
BF - Biotechnical Faculty
Publication status:Published
Publication version:Version of Record
Year:2019
Number of pages:7 str.
Numbering:Vol. 10, art. 4551
PID:20.500.12556/RUL-125567 This link opens in a new window
UDC:004.9:577
ISSN on article:2041-1723
DOI:10.1038/s41467-019-12397-x This link opens in a new window
COBISS.SI-ID:32755751 This link opens in a new window
Publication date in RUL:25.03.2021
Views:2045
Downloads:354
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Record is a part of a journal

Title:Nature communications
Shortened title:Nat. Commun.
Publisher:Nature Publishing Group
ISSN:2041-1723
COBISS.SI-ID:2315876 This link opens in a new window

Licences

License:CC BY 4.0, Creative Commons Attribution 4.0 International
Link:http://creativecommons.org/licenses/by/4.0/
Description:This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.
Licensing start date:25.03.2021

Projects

Funder:ARRS - Slovenian Research Agency
Project number:P2-0209
Name:Umetna inteligenca in inteligentni sistemi

Funder:ARRS - Slovenian Research Agency
Project number:BI-US/17-18-014

Funder:ARRS - Slovenian Research Agency
Project number:P1-0207
Name:Toksini in biomembrane

Funder:ARRS - Slovenian Research Agency
Project number:N1-0034
Name:Medsebojni vpliv med lipidnim in osrednjim ogljikovim metabolizmom

Funder:NIH - National Institutes of Health
Project number:R35 GM118016

Funder:NIH - National Institutes of Health
Funding programme:National Institute of Arthritis and Musculoskeletal and Skin Diseases
Project number:R01AR072018

Funder:Other - Other funder or multiple funders
Funding programme:Italian Ministry of Education, University and Research
Name:Dipartimenti di Eccelenza Program (2018-2022)

Funder:Other - Other funder or multiple funders
Funding programme:Fondazione Regionale per la Ricerca Biomedica
Project number:2015-0042

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