Data Validation in Cancer Imaging Repositories: the INCISIVE Approach<sup>*</sup>-Reference-Cited by-同舟云学术

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Data Validation in Cancer Imaging Repositories: the INCISIVE Approach^*

Published:2023-12-07 Issue: Volume: Page:75-76
ISSN:
Container-title:2023 IEEE EMBS Special Topic Conference on Data Science and Engineering in Healthcare, Medicine and Biology
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Author:

Tsave O.¹,Kosvyra A.²,Filos D.²,Lazic I³,Loncar-Turukalo T.³,Jakovljevic N.³,Xinou E.⁴,Fotopoulos D.²,Zacharias L.⁵,Nabhani-Gebara Sh.⁵,Tsakou G.⁶,Chouvarda I.²

Affiliation:

1. Aristotle University of Thessaloniki,School of Medicine,Greece

2. Aristotle University of Thessaloniki,School of Medicine,54124, Greece

3. University of Novi Sad,Faculty of Technical Sciences,Serbia

4. Theagenion Anticancer Hospital of Thessaloniki,Department of Diagnostic Radiology,54007, Thessaloniki,Greece

5. Kingston University London,Department of Pharmacy,London KT1 2EE,UK

6. Research and Development Lab,MAGGIOLI S.P.A.,Marousi,Greece

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10404092/10404107/10404109.pdf?arnumber=10404109

Reference4 articles.

1. The Holistic Perspective of the INCISIVE Project—Artificial Intelligence in Screening Mammography

2. Data Quality Check in Cancer Imaging Research: Deploying and Evaluating the DIQCT Tool

3. A framework for validating AI in precision medicine: considerations from the European ITFoC consortium

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