1. Ktisis Cyprus University of Technology
  2. Cyprus University of Technology (Research Output)
  3. Άρθρα/Articles
Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/29663
DC FieldValueLanguage
dc.contributor.authorLazic, Ivan-
dc.contributor.authorAgullo, Ferran-
dc.contributor.authorAusso, Susanna-
dc.contributor.authorAlves, Bruno-
dc.contributor.authorBarelle, Caroline-
dc.contributor.authorBerral, Josep Ll-
dc.contributor.authorBizopoulos, Paschalis-
dc.contributor.authorBunduc, Oana-
dc.contributor.authorChouvarda, Ioanna-
dc.contributor.authorDominguez, Didier-
dc.contributor.authorFilos, Dimitrios-
dc.contributor.authorGutierrez-Torre, Alberto-
dc.contributor.authorHesso, Iman-
dc.contributor.authorJakovljević, Nikša-
dc.contributor.authorKayyali, Reem-
dc.contributor.authorKogut-Czarkowska, Magdalena-
dc.contributor.authorKosvyra, Alexandra-
dc.contributor.authorLalas, Antonios-
dc.contributor.authorLavdaniti, Maria-
dc.contributor.authorLoncar-Turukalo, Tatjana-
dc.contributor.authorMartinez-Alabart, Sara-
dc.contributor.authorMichas, Nassos-
dc.contributor.authorNabhani-Gebara, Shereen-
dc.contributor.authorRaptopoulos, Andreas-
dc.contributor.authorRoussakis, Yiannis-
dc.contributor.authorStalika, Evaggelia-
dc.contributor.authorSymvoulidis, Chrysostomos-
dc.contributor.authorTsave, Olga-
dc.contributor.authorVotis, Konstantinos-
dc.contributor.authorCharalambous, Andreas-
dc.date.accessioned2023-07-05T10:58:14Z-
dc.date.available2023-07-05T10:58:14Z-
dc.date.issued2022-09-01-
dc.identifier.citationApplied Sciences (Switzerland), 2022, vol. 12, no. 17, pp. 1-29en_US
dc.identifier.issn20763417-
dc.identifier.urihttps://hdl.handle.net/20.500.14279/29663-
dc.description.abstractFinding 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.en_US
dc.formatPdfen_US
dc.language.isoenen_US
dc.relation.ispartofApplied Sciences (Switzerland)en_US
dc.rights© by the authorsen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/-
dc.subjectMedical imagesen_US
dc.subjectMammographyen_US
dc.subjectArtificial intelligenceen_US
dc.subjectDeep learningen_US
dc.subjectHealth data sharingen_US
dc.titleThe Holistic Perspective of the INCISIVE Project—Artificial Intelligence in Screening Mammographyen_US
dc.typeArticleen_US
dc.collaborationUniversity of Novi Saden_US
dc.collaborationBarcelona Supercomputing Centeren_US
dc.collaborationMinistry of Health of Cataloniaen_US
dc.collaborationEuropean Dynamicsen_US
dc.collaborationCentre for Research and Technology Hellas (CERTH)en_US
dc.collaborationTelesto IoT Solutionsen_US
dc.collaborationAristotle University of Thessalonikien_US
dc.collaborationKingston University Londonen_US
dc.collaborationTimelex BV/SRLen_US
dc.collaborationInternational Hellenic Universityen_US
dc.collaborationHellenic Cancer Societyen_US
dc.collaborationEuropean Dynamicsen_US
dc.collaborationGerman Oncology Centeren_US
dc.collaborationUniversity of Piraeusen_US
dc.collaborationCyprus University of Technologyen_US
dc.subject.categoryMEDICAL AND HEALTH SCIENCESen_US
dc.journalsOpen Accessen_US
dc.countryCyprusen_US
dc.countrySerbiaen_US
dc.countrySpainen_US
dc.countryLuxembourgen_US
dc.countryGreeceen_US
dc.countryUnited Kingdomen_US
dc.countryBelgiumen_US
dc.subject.fieldMedical and Health Sciencesen_US
dc.publicationPeer Revieweden_US
dc.identifier.doi10.3390/app12178755en_US
dc.identifier.scopus2-s2.0-85137897826-
dc.identifier.urlhttps://api.elsevier.com/content/abstract/scopus_id/85137897826-
dc.relation.issue17en_US
dc.relation.volume12en_US
cut.common.academicyear2022-2023en_US
dc.identifier.spage1en_US
dc.identifier.epage29en_US
item.grantfulltextopen-
item.languageiso639-1en-
item.cerifentitytypePublications-
item.openairecristypehttp://purl.org/coar/resource_type/c_6501-
item.openairetypearticle-
item.fulltextWith Fulltext-
crisitem.author.deptDepartment of Nursing-
crisitem.author.facultyFaculty of Health Sciences-
crisitem.author.orcid0000-0003-4050-031X-
crisitem.author.parentorgFaculty of Health Sciences-
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