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these are known to be computationally expensive due to the density estimation step. In contrast, our proposed DRN with LSMI formulation does not require the density estimation step and can be used as an alternative to approximate mutual information. Experiments on the CT based COVID-19 Detection and COVID-19 Severity Detection Challenges of the 2nd COV19D competition  demonstrate the effectiveness of our method compared to the baseline method of such competition.
|Title of host publication||Lecture Notes in Computer Science|
|Subtitle of host publication||Computer Vision – ECCV 2022 Workshops|
|Editors||Leonid Karlinsky, Tomer Michaeli, Ko Nishino|
|Number of pages||16|
|Publication status||Published - 23 Feb 2023|
|Name||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|
Bibliographical noteFunding Information:
Acknowledgement. We want to thank the organizers of the 2nd COV19D Competition occurring in the ECCV 2022 Workshop: AI-enabled Medical Image Analysis - Digital Pathology & Radiology/COVID19 for providing access to extensive and high-quality data to benchmark our model. This research has been partially financed by the European Union under the Horizon 2020 Research and Innovation programme under grant agreement 101016131 (ICOVID).
© 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
- Representation learning
- mutual information
- COVID-19 detection
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VLIR409: (COVID-19 PROMPT) Toward PrecisiOn Medicine for the Prediction of Treatment response to Covid-19 in Cuba
1/09/22 → 31/08/24
1/09/20 → 28/02/23
- 2 Article
Diaz Berenguer, A., Mukherjee, T., Bossa Bossa, M. N., Deligiannis, N. & Sahli, H., 4 Jul 2022, In: ArXiv.org. 2022, p. 1-10 10 p.
Research output: Contribution to journal › Article
Explainable-by-design Semi-Supervised Representation Learning for COVID-19 Diagnosis from CT ImagingBerenguer, A. D., Sahli, H., Joukovsky, B., Kvasnytsia, M., Dirks, I., Alioscha-Perez, M., Deligiannis, N., Gonidakis, P., Sánchez, S. A., Brahimetaj, R., Papavasileiou, E., Chana, J. C-W., Li, F., Song, S., Yang, Y., Tilborghs, S., Willems, S., Eelbode, T., Bertels, J., Vandermeulen, D. & 20 others, , 2 Dec 2020, In: ArXiv.org. 2020, 20 p.
Research output: Contribution to journal › ArticleFile
- 1 Talk or presentation at a conference