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2022 Conference article Open Access OPEN
Exemplars and counterexemplars explanations for skin lesion classifiers
Metta C., Guidotti R., Yin Y., Gallinari P., Rinzivillo S.
Explainable AI consists in developing models allowing interaction between decision systems and humans by making the decisions understandable. We propose a case study for skin lesion diagnosis showing how it is possible to provide explanations of the decisions of deep neural network trained to label skin lesions.Source: HHAI2022 - Augmenting Human Intellect, pp. 258–260, Amsterdam, The Netherlands, 13-17/07/2022
DOI: 10.3233/faia220209
Project(s): HumanE-AI-Net via OpenAIRE
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See at: ebooks.iospress.nl Open Access | ISTI Repository Open Access | CNR ExploRA Open Access


2021 Conference article Restricted
Exemplars and counterexemplars explanations for image classifiers, targeting skin lesion labeling
Metta C., Guidotti R., Yin Y., Gallinari P., Rinzivillo S.
Explainable AI consists in developing mechanisms allowing for an interaction between decision systems and humans by making the decisions of the formers understandable. This is particularly important in sensitive contexts like in the medical domain. We propose a use case study, for skin lesion diagnosis, illustrating how it is possible to provide the practitioner with explanations on the decisions of a state of the art deep neural network classifier trained to characterize skin lesions from examples. Our framework consists of a trained classifier onto which an explanation module operates. The latter is able to offer the practitioner exemplars and counterexemplars for the classification diagnosis thus allowing the physician to interact with the automatic diagnosis system. The exemplars are generated via an adversarial autoencoder. We illustrate the behavior of the system on representative examples.Source: ISCC 2021 - IEEE Symposium on Computers and Communications, Athens, Greece, 5-8/09/2021
DOI: 10.1109/iscc53001.2021.9631485
Project(s): AI4EU via OpenAIRE, TAILOR via OpenAIRE, HumanE-AI-Net via OpenAIRE
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See at: doi.org Restricted | ieeexplore.ieee.org Restricted | CNR ExploRA Restricted