Automatic Classification of Proximal Femur Fractures Based on Attention Models. - Anees Kazi; Shadi Albarqouni; Amelia Jiménez-Sánchez; Sonja Kirchhoff; Peter Biberthaler; Nassir Navab; Diana Mateus (MLMI@MICCAI, 2017)

Capsule Networks Against Medical Imaging Data Challenges. - Amelia Jiménez-Sánchez; Shadi Albarqouni; Diana Mateus (CVII-STENT/LABELS@MICCAI, 2018)

Weakly-Supervised Localization and Classification of Proximal Femur Fractures. - Amelia Jiménez-Sánchez; Anees Kazi; Shadi Albarqouni; Sonja Kirchhoff; Alexandra Sträter; Peter Biberthaler; Diana Mateus; Nassir Navab (CoRR, 2018)

Medical-based Deep Curriculum Learning for Improved Fracture Classification. - Amelia Jiménez-Sánchez; Diana Mateus; Sonja Kirchhoff; Chlodwig Kirchhoff; Peter Biberthaler; Nassir Navab; Miguel Ángel González Ballester; Gemma Piella (MICCAI (6), 2019)

Towards an Interactive and Interpretable CAD System to Support Proximal Femur Fracture Classification. - Amelia Jiménez-Sánchez; Anees Kazi; Shadi Albarqouni; Chlodwig Kirchhoff; Peter Biberthaler; Nassir Navab; Diana Mateus; Sonja Kirchhoff (CoRR, 2019)

Precise proximal femur fracture classification for interactive training and surgical planning. - Amelia Jiménez-Sánchez; Anees Kazi; Shadi Albarqouni; Chlodwig Kirchhoff; Peter Biberthaler; Nassir Navab; Sonja Kirchhoff; Diana Mateus (Int. J. Comput. Assist. Radiol. Surg., 2020)

Curriculum learning for annotation-efficient medical image analysis: scheduling data with prior knowledge and uncertainty. - Amelia Jiménez-Sánchez; Diana Mateus; Sonja Kirchhoff; Chlodwig Kirchhoff; Peter Biberthaler; Nassir Navab; Miguel Ángel González Ballester; Gemma Piella (CoRR, 2020)

Learning representations for medical image diagnosis: impact of curriculum training and architectural design. - Amelia Jiménez-Sánchez (2021)

Curriculum learning for improved femur fracture classification: Scheduling data with prior knowledge and uncertainty. - Amelia Jiménez-Sánchez; Diana Mateus; Sonja Kirchhoff; Chlodwig Kirchhoff; Peter Biberthaler; Nassir Navab; Miguel Ángel González Ballester; Gemma Piella (Medical Image Anal., 2022)

Detecting Shortcuts in Medical Images - A Case Study in Chest X-Rays. - Amelia Jiménez-Sánchez; Dovile Juodelyte; Bethany Chamberlain; Veronika Cheplygina (ISBI, 2023)

Revisiting Hidden Representations in Transfer Learning for Medical Imaging. - Dovile Juodelyte; Amelia Jiménez-Sánchez; Veronika Cheplygina (Trans. Mach. Learn. Res., 2023)

Memory-aware curriculum federated learning for breast cancer classification. - Amelia Jiménez-Sánchez; Mickael Tardy; Miguel Ángel González Ballester; Diana Mateus; Gemma Piella (Comput. Methods Programs Biomed., 2023)

Source Matters: Source Dataset Impact on Model Robustness in Medical Imaging. - Dovile Juodelyte; Yucheng Lu; Amelia Jiménez-Sánchez; Sabrina Bottazzi; Enzo Ferrante; Veronika Cheplygina (AMAI@MICCAI, 2024)

[Citation needed] Data usage and citation practices in medical imaging conferences. - Théo Sourget; Ahmet Akkoç; Stinna Winther; Christine Lyngbye Galsgaard; Amelia Jiménez-Sánchez; Dovile Juodelyte; Caroline Petitjean; Veronika Cheplygina (MIDL, 2024)

Copycats: the many lives of a publicly available medical imaging dataset. - Amelia Jiménez-Sánchez; Natalia Rozalia Avlona; Dovile Juodelyte; Théo Sourget; Caroline Vang-Larsen; Anna Rogers; Hubert Dariusz Zajac; Veronika Cheplygina (NeurIPS, 2024)

Towards actionability for open medical imaging datasets: lessons from community-contributed platforms for data management and stewardship. - Amelia Jiménez-Sánchez; Natalia Rozalia Avlona; Dovile Juodelyte; Théo Sourget; Caroline Vang-Larsen; Hubert Dariusz Zajac; Veronika Cheplygina (CoRR, 2024)

Mask of truth: model sensitivity to unexpected regions of medical images. - Théo Sourget; Michelle Hestbek-Møller; Amelia Jiménez-Sánchez; Jack Junchi Xu; Veronika Cheplygina (CoRR, 2024)

In the Picture: Medical Imaging Datasets, Artifacts, and their Living Review. - Amelia Jiménez-Sánchez; Natalia Rozalia Avlona; Sarah de Boer; Víctor M. Campello; Aasa Feragen; Enzo Ferrante; Melanie Ganz; Judy Wawira Gichoya; Camila González; Steff Groefsema; Alessa Hering; Adam Hulman; et al. (FAccT, 2025)

Augmenting Chest X-ray Datasets with Non-Expert Annotations. - Veronika Cheplygina; Cathrine Damgaard; Trine Naja Eriksen; Dovile Juodelyte; Amelia Jiménez-Sánchez (MIUA (1), 2025)