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Applied Sciences (Switzerland)Volume 12, Issue 17, September 2022, Article number 8755

The Holistic Perspective of the INCISIVE Project—Artificial Intelligence in Screening Mammography(Article)(Open Access)

  • Lazic, I.,
  • Agullo, F.,
  • Ausso, S.,
  • Alves, B.,
  • Barelle, C.,
  • Berral, J.L.,
  • Bizopoulos, P.,
  • Bunduc, O.,
  • Chouvarda, I.,
  • Dominguez, D.,
  • Filos, D.,
  • Gutierrez-Torre, A.,
  • Hesso, I.,
  • Jakovljević, N.,
  • Kayyali, R.,
  • Kogut-Czarkowska, M.,
  • Kosvyra, A.,
  • Lalas, A.,
  • Lavdaniti, M.,
  • Loncar-Turukalo, T.,
  • Martinez-Alabart, S.,
  • Michas, N.,
  • Nabhani-Gebara, S.,
  • Raptopoulos, A.,
  • Roussakis, Y.,
  • Stalika, E.,
  • Symvoulidis, C.,
  • Tsave, O.,
  • Votis, K.,
  • Charalambous, A.
  • View Correspondence (jump link)
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  • aFaculty of Technical Sciences, University of Novi Sad, Novi Sad, 21000, Serbia
  • bBarcelona Supercomputing Center, Barcelona, 08034, Spain
  • cFundació TIC Salut Social, Ministry of Health of Catalonia, Barcelona, 08005, Spain
  • dEuropean Dynamics, Luxembourg, 1466, Luxembourg
  • eCentre for Research and Technology Hellas, Thessaloniki, 57001, Greece
  • fTelesto IoT Solutions, London, N7 7PX, United Kingdom
  • gSchool of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, Thessaloniki, 54124, Greece
  • hDepartment of Pharmacy, Kingston University London, London, KT1 2EE, United Kingdom
  • iTimelex BV/SRL, Brussels, 1000, Belgium
  • jNursing Department, International Hellenic University, Thessaloniki, 57400, Greece
  • kHellenic Cancer Society, Athens, 11521, Greece
  • lEuropean Dynamics, Athens, 15124, Greece
  • mGerman Oncology Center, Department of Medical Physics, Limassol, 4108, Cyprus
  • nDepartment of Digital Systems, University of Piraeus, Piraeus, 18534, Greece
  • oDepartment of Nursing, Cyprus University of Technology, Limassol, 3036, Cyprus

Abstract

Finding new ways to cost-effectively facilitate population screening and improve cancer diagnoses at an early stage supported by data-driven AI models provides unprecedented opportunities to reduce cancer related mortality. This work presents the INCISIVE project initiative towards enhancing AI solutions for health imaging by unifying, harmonizing, and securely sharing scattered cancer-related data to ensure large datasets which are critically needed to develop and evaluate trustworthy AI models. The adopted solutions of the INCISIVE project have been outlined in terms of data collection, harmonization, data sharing, and federated data storage in compliance with legal, ethical, and FAIR principles. Experiences and examples feature breast cancer data integration and mammography collection, indicating the current progress, challenges, and future directions. © 2022 by the authors.

Author keywords

artificial intelligencedeep learninghealth data sharingmammographymedical images

Funding details

Funding sponsor Funding number Acronym
Horizon 2020 Framework Programme
See opportunities by H2020		952179H2020
Horizon 2020 Framework Programme
See opportunities by H2020		H2020
Ministerio de Asuntos Económicos y Transformación Digital, Gobierno de España2017-SGR-1414,PID2019-107255GBMINECO
Ministerio de Asuntos Económicos y Transformación Digital, Gobierno de EspañaMINECO

  • 1

    This research received funding mainly from the European Union’s Horizon 2020 research and innovation program under grant agreement no 952179. It was also partially funded by the Ministry of Economy, Industry, and Competitiveness of Spain under contracts PID2019-107255GB and 2017-SGR-1414.

  • ISSN: 20763417
  • Source Type: Journal
  • Original language: English
  • DOI: 10.3390/app12178755
  • Document Type: Article
  • Publisher: MDPI

  Bunduc, O.; Telesto IoT Solutions, London, United Kingdom;
© Copyright 2022 Elsevier B.V., All rights reserved.

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