Reinforcement Learning for Active Modality Selection During Diagnosis-Reference-Cited by-同舟云学术

Reinforcement Learning for Active Modality Selection During Diagnosis

Published:2022 Issue: Volume: Page:592-601
ISSN:0302-9743
Container-title:Lecture Notes in Computer Science
language:
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Author:

Bernardino Gabriel^ORCID,Jonsson Anders^ORCID,Loncaric Filip^ORCID,Martí Castellote Pablo-Miki^ORCID,Sitges Marta^ORCID,Clarysse Patrick^ORCID,Duchateau Nicolas^ORCID

Publisher

Springer Nature Switzerland

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-16431-6_56

Reference13 articles.

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2. Lecture Notes in Computer Science;G Bernardino,2022

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4. Garbi, M., et al.: EACVI appropriateness criteria for the use of cardiovascular imaging in heart failure derived from European National Imaging Societies voting. Europ. Heart J. Cardiovascular Imaging 17(7), 711–721 (2016)

5. Gong, W., et al.: Icebreaker: Element-wise Efficient Information Acquisition with a Bayesian Deep Latent Gaussian Model. In: Wallach, H., Larochelle, H., Beygelzimer, A., Alché-Buc, F., Fox, E., Garnett, R. (eds.) Advances in Neural Information Processing Systems, vol. 32. Curran Associates, Inc. (2019)

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