Amelia Jiménez-Sánchez
Amelia is a Postdoctoral Researcher at the IT University of Copenhagen. Her research interests are in the broad areas of medical imaging, representation learning and data science. She has experience developing algorithms to deal with label noise, limited amounts of data and class-imbalance, problems that are fairly common in medical datasets. She is working on the project “Making Metadata Count”. Before joining ITU, she received a degree in Telecommunications Engineering from the University of Granada, a Master of Science in Biomedical Computing from the Technical University of Munich and her Ph.D. from Pompeu Fabra University. Find more info on https://ameliajimenez.github.io/
References
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Source Matters: Source Dataset Impact on Model Robustness in Medical ImagingarXiv preprint arXiv:2403.04484, 2024 -
Towards actionability for open medical imaging datasets: lessons from community-contributed platforms for data management and stewardshiparXiv preprint arXiv:2402.06353, 2024 -
Revisiting Hidden Representations in Transfer Learning for Medical ImagingTransactions on Machine Learning Research, 2023 -
Augmenting Chest X-ray Datasets with Non-Expert AnnotationsarXiv preprint arXiv:2309.02244, 2023 -
Memory-aware curriculum federated learning for breast cancer classificationComputer Methods and Programs in Biomedicine, 2022 -
Detecting Shortcuts in Medical Images – A Case Study in Chest X-rays2022
