Marta Ligero
Identifiers
- name variant Marta Ligero 0.60 · backfill
Papers (7)
- Three-dimensional end-to-end deep learning for brain MRI analysis cs.CV · 2025 · author #2
- Abnormality-Driven Representation Learning for Radiology Imaging cs.CV · 2024 · author #1
- Unsupervised Foundation Model-Agnostic Slide-Level Representation Learning cs.CV · 2024 · author #3
- In-context learning enables multimodal large language models to classify cancer pathology images cs.CV · 2024 · author #4
- Reducing self-supervised learning complexity improves weakly-supervised classification performance in computational pathology cs.LG · 2024 · author #3
- Joint multi-task learning improves weakly-supervised biomarker prediction in computational pathology eess.IV · 2024 · author #3
- From Whole-slide Image to Biomarker Prediction: A Protocol for End-to-End Deep Learning in Computational Pathology cs.CV · 2023 · author #5
Mentions
- 2506.23916 #2 · arxiv_oai · confidence 0.70 Marta Ligero
- 2411.13623 #3 · arxiv_oai · confidence 0.70 Marta Ligero
- 2411.16803 #1 · arxiv_oai · confidence 0.70 Marta Ligero
- 2403.07407 #4 · arxiv_oai · confidence 0.70 Marta Ligero
- 2403.04558 #3 · arxiv_oai · confidence 0.70 Marta Ligero
- 2403.03891 #3 · arxiv_oai · confidence 0.70 Marta Ligero
- 2312.10944 #5 · arxiv_oai · confidence 0.70 Marta Ligero
Frequent Coauthors
- Jakob Nikolas Kather 7 shared papers
- Tim Lenz 6 shared papers
- Daniel Truhn 5 shared papers
- Georg W\"olflein 5 shared papers
- Marko van Treeck 3 shared papers
- Omar S. M. El Nahhas 3 shared papers
- Firas Khader 2 shared papers
- Omar S.M. El Nahhas 2 shared papers
- Asier Rabasco 1 shared papers
- Dirk J\"ager 1 shared papers
- Dyke Ferber 1 shared papers
- Gregory Patrick Veldhuizen 1 shared papers
- Gustav M\"uller-Franzes 1 shared papers
- Hagen H. Kitzler 1 shared papers
- Isabella C. Wiest 1 shared papers
- Katherine J. Hewitt 1 shared papers
- Leo Misera 1 shared papers
- Michaela Unger 1 shared papers
- Narmin Ghaffari Laleh 1 shared papers
- Paul Kuntke 1 shared papers