End-to-End Deep Learning Vector Autoregressive Prognostic Models to Predict Disease Progression with Uneven Time Intervals-Reference-Cited by-同舟云学术

End-to-End Deep Learning Vector Autoregressive Prognostic Models to Predict Disease Progression with Uneven Time Intervals

Published:2021 Issue: Volume: Page:517-531
ISSN:0302-9743
Container-title:Medical Image Understanding and Analysis
language:
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Author:

Bridge Joshua,Harding Simon,Zheng Yalin

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-030-80432-9_38

Reference38 articles.

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4. Arenja, N., et al.: Prognostic value of novel imaging parameters derived from standard cardiovascular magnetic resonance in high risk patients with systemic light chain amyloidosis. J. Cardiovasc. Magn. Reson. 21(1), 53 (2019). https://doi.org/10.1186/s12968-019-0564-1

5. Babenko, B., et al.: Predicting progression of age-related macular degeneration from fundus images using deep learning (2019). arXiv preprint arXiv:1904.05478

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