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

Journal
Applied Sciences (Switzerland)
Date Issued
September 1, 2022
Author(s)
Lazic, Ivan  
Agullo, Ferran  
Ausso, Susanna  
Alves, Bruno  
Barelle, Caroline  
Berral, Josep Ll  
Bizopoulos, Paschalis  
Bunduc, Oana  
Chouvarda, Ioanna  
Dominguez, Didier  
Filos, Dimitrios  
Gutierrez-Torre, Alberto  
Hesso, Iman  
Jakovljević, Nikša  
Kayyali, Reem  
Kogut-Czarkowska, Magdalena  
Kosvyra, Alexandra  
Lalas, Antonios  
Lavdaniti, Maria  
Loncar-Turukalo, Tatjana  
Martinez-Alabart, Sara  
Michas, Nassos  
Nabhani-Gebara, Shereen  
Raptopoulos, Andreas  
Roussakis, Yiannis  
Stalika, Evaggelia  
Symvoulidis, Chrysostomos  
Tsave, Olga  
Votis, Konstantinos  
Charalambous, Andreas  
DOI
10.3390/app12178755
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.
Subjects

Medical images

Mammography

Artificial intelligen...

Deep learning

Health data sharing

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Thumbnail Image
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applsci-12-08755-v2.pdf

Size

4.5 MB

Format

Adobe PDF

Checksum (MD5)

6f3ecf3833543edc26d0882070c28d27

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