EXplainable Artificial Intelligence (XAI) recently emerged as one of the hottest topics aimed at overcoming this limitation by proposing strategies for understanding the why and the how of the outcomes of Machine (ML) and Deep Learning (DL), allowing to disentangle the contributions of the different features of the input shaping the CNN final output.
Explainable deep learning for decrypting disease signatures in multiple sclerosis
Federica Cruciani
;Lorenza Brusini;Mauro Zucchelli;Gustavo Retuci Pinheiro;Francesco Setti;Rachid Deriche;Leticia Rittner;Massimiliano Calabrese;Ilaria Boscolo Galazzo;Gloria Menegaz
2023-01-01
Abstract
EXplainable Artificial Intelligence (XAI) recently emerged as one of the hottest topics aimed at overcoming this limitation by proposing strategies for understanding the why and the how of the outcomes of Machine (ML) and Deep Learning (DL), allowing to disentangle the contributions of the different features of the input shaping the CNN final output.
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