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

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 solu...

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Detalhes bibliográficos

Principais autores:	Ivan Lazic, Ferran Agullo, Susanna Ausso, Bruno Alves, Caroline Barelle, Josep Ll. Berral, Paschalis Bizopoulos, Oana Bunduc, Ioanna Chouvarda, Didier Dominguez, Dimitrios Filos, Alberto Gutierrez-Torre, Iman Hesso, Nikša Jakovljević, Reem Kayyali, Magdalena Kogut-Czarkowska, Alexandra Kosvyra, Antonios Lalas, Maria Lavdaniti, Tatjana Loncar-Turukalo, Sara Martinez-Alabart, Nassos Michas, Shereen Nabhani-Gebara, Andreas Raptopoulos, Yiannis Roussakis, Evangelia Stalika, Chrysostomos Symvoulidis, Olga Tsave, Konstantinos Votis, Andreas Charalambous
Formato:	Artigo
Idioma:	Inglês
Publicado em:	MDPI AG 2022-08-01
Colecção:	Applied Sciences
Assuntos:	medical images mammography artificial intelligence deep learning health data sharing
Acesso em linha:	https://www.mdpi.com/2076-3417/12/17/8755
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