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Barbara Noris Chiorda on Muck Rack

Barbara Noris Chiorda

As seen in: Nature
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Articles

Exploring self-supervised deep sparse autoencoders for robust feature selection in radiomics analysis

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By Sithin Thulasi Seetha, Antonella Messina, Alessandra Casale, Enrico Garanzini, Chiara Tenconi, Cristina Marenghi, Fabio Badenchini, Barbara Avuzzi, Mario Achille Catanzaro, Nicola Nicolai, Silvia Stagni, Sergio Isaza Villa, Andre Dekker, Tiziana Rancati, Barbara Noris Chiorda
| Nature Verified
Abstract While considerable effort has been devoted to examining how variations in study protocols, acquisition settings, and annotations influence radiomics features, the role of feature selection (FS) methods largely remains unexplored. This study investigates a self-supervised deep sparse autoencoder ensemble (ensembleAE) and a novel Bayesian variant (bayesianAE) for radiomics FS in a small, class-imbalanced framework.
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