Research output per year
Research output per year
Project Details
Description
This icovid project is the continuation of the pro bono icovid initiative that developed the CE-marked and FDA permitted AIbased CT analysis software, icolung, and made it available in over 65 hospitals worldwide.
Funding Acknowledgement(s)
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No [Number]
| Short title or EU acronym | icovid |
|---|---|
| Acronym | EUAR46 |
| Status | Finished |
| Effective start/end date | 1/09/20 → 28/02/23 |
Flemish discipline codes in use since 2023
- Artificial intelligence not elsewhere classified
Fingerprint
Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint.
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The STOIC2021 COVID-19 AI challenge: applying reusable training methodologies to private data
Boulogne, L. H., Lorenz, J., Kienzle, D., Schon, R., Ludwig, K., Lienhart, R., Jegou, S., Li, G., Chen, C., Wang, Q., Shi, D., Maniparambil, M., Muller, D., Mertes, S., Schroter, N., Hellmann, F., Elia, M., Dirks, I., Bossa, M. N., Berenguer, A. D. & 18 others, , Oct 2024, In: Medical Image Analysis. 97, 24 p., 103230.Research output: Contribution to journal › Article › peer-review
Open Access2 Citations (Scopus)10 Downloads (Pure) -
Representation Learning with Information Theory to Detect COVID-19 and its Severity
Diaz Berenguer, A., Mukherjee, T., Da, Y., Bossa Bossa, M. N., Kvasnytsia, M., Vandemeulebroucke, J., Deligiannis, N. & Sahli, H., 23 Feb 2023, Lecture Notes in Computer Science: Computer Vision – ECCV 2022 Workshops. Karlinsky, L., Michaeli, T. & Nishino, K. (eds.). Springer, Cham, Vol. 13807. p. 605-620 16 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 13807 LNCS).Research output: Chapter in Book/Report/Conference proceeding › Chapter › Research › peer-review
1 Citation (Scopus) -
Representation Learning with Information Theory for COVID-19 Detection
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
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Medical imaging-based Diagnosis & Prognosis with application to COVID-19 Detection from CT imaging.
Abel Diaz Berenguer (Speaker)
26 Aug 2022Activity: Talk or presentation › Talk at a school event
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Representation Learning with Information Theory to Detect COVID-19 and its Severity
Abel Diaz Berenguer (Speaker)
24 Oct 2022Activity: Talk or presentation › Talk or presentation at a conference