Empowering digital pathology applications through explainable knowledge extraction tools

Empowering digital pathology applications through explainable knowledge extraction tools

Exa-scale volumes of medical data have been produced for decades. In most cases, the diagnosis is reported in free text, encoding medical knowledge that is still largely unexploited. In order to allow decoding medical knowledge included in reports, we propose an unsupervised knowledge extraction sys...

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Bibliographic Details
Main Authors:	Stefano Marchesin, Fabio Giachelle, Niccolò Marini, Manfredo Atzori, Svetla Boytcheva, Genziana Buttafuoco, Francesco Ciompi, Giorgio Maria Di Nunzio, Filippo Fraggetta, Ornella Irrera, Henning Müller, Todor Primov, Simona Vatrano, Gianmaria Silvello
Format:	Article
Language:	English
Published:	Elsevier 2022-01-01
Series:	Journal of Pathology Informatics
Subjects:	Clinical practice Digital pathology Expert systems Explainable AI Knowledge extraction Machine learning
Online Access:	http://www.sciencedirect.com/science/article/pii/S2153353922007337

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