Abstract
In this paper, we advocate that combining several frameworks in artificial intelligence, adopting a hybrid point of view for both knowledge data representation and reasoning, offers opportunities towards explainability. This idea is illustrated on the example of image understanding, in particular in medical imaging, formulated as a spatial reasoning problem.
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CITATION STYLE
Bloch, I. (2022). Hybrid Artificial Intelligence for Knowledge Representation and Model-Based Medical Image Understanding - Towards Explainability. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 13493 LNCS, pp. 17–25). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-19897-7_2
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