Amelia Jiménez-Sánchez

According to our database, Amelia Jiménez-Sánchez authored at least 16 papers between 2017 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Source Matters: Source Dataset Impact on Model Robustness in Medical Imaging.

Dovile Juodelyte, Yucheng Lu, Amelia Jiménez-Sánchez, Sabrina Bottazzi, Enzo Ferrante, Veronika Cheplygina

CoRR, 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

[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

CoRR, 2024

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., February, 2023

Augmenting Chest X-ray Datasets with Non-Expert Annotations.

Cathrine Damgaard, Trine Naja Eriksen, Dovile Juodelyte, Veronika Cheplygina, Amelia Jiménez-Sánchez

CoRR, 2023

Revisiting Hidden Representations in Transfer Learning for Medical Imaging.

Dovile Juodelyte, Amelia Jiménez-Sánchez, Veronika Cheplygina

CoRR, 2023

Detecting Shortcuts in Medical Images - A Case Study in Chest X-Rays.

Amelia Jiménez-Sánchez, Dovile Juodelyte, Bethany Chamberlain, Veronika Cheplygina

Proceedings of the 20th IEEE International Symposium on Biomedical Imaging, 2023

2022

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

2021

Learning representations for medical image diagnosis: impact of curriculum training and architectural design.

Amelia Jiménez-Sánchez

PhD thesis, 2021

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

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

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

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

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2019, 2019

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

Capsule Networks Against Medical Imaging Data Challenges.

Amelia Jiménez-Sánchez, Shadi Albarqouni, Diana Mateus

Proceedings of the Intravascular Imaging and Computer Assisted Stenting - and - Large-Scale Annotation of Biomedical Data and Expert Label Synthesis, 2018

2017

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

Proceedings of the Machine Learning in Medical Imaging - 8th International Workshop, 2017