Lorena Escudero Sanchez

According to our database, Lorena Escudero Sanchez authored at least 10 papers between 2021 and 2026.

Collaborative distances:

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

2026

Developing Predictive and Robust Radiomics Models for Chemotherapy Response in High-Grade Serous Ovarian Carcinoma.

Sepideh Hatamikia, Geevarghese George, Florian Schwarzhans, Amirreza Mahbod, Marika Reinius, Ali Abbasian Ardakani, Mercedes Jimenez-Linan, Satish Viswanath, Mireia Crispin-Ortuzar, Lorena Escudero Sanchez, Evis Sala, James D. Brenton, Ramona Woitek

CoRR, January, 2026

2025

Submanifold Sparse Convolutional Networks for Automated 3D Segmentation of Kidneys and Kidney Tumours in Computed Tomography.

Saúl Alonso-Monsalve, Leigh H. Whitehead, Adam Aurisano, Lorena Escudero Sanchez

CoRR, November, 2025

A European Multi-Center Breast Cancer MRI Dataset.

Gustav Müller-Franzes, Lorena Escudero Sanchez, Nicholas Payne, Alexandra Athanasiou, Michael Kalogeropoulos, Aitor Lopez, Alfredo Miguel Soro Busto, Julia Camps Herrero, Nika Rasoolzadeh, Tianyu Zhang, Ritse Mann, Debora Jutz, Maike Bode, Christiane Kuhl, Wouter Veldhuis, Oliver Lester Saldanha, Jiefu Zhu, Jakob Nikolas Kather, Daniel Truhn, Fiona J. Gilbert

CoRR, June, 2025

2023

Calibrating ensembles for scalable uncertainty quantification in deep learning-based medical image segmentation.

Thomas Buddenkotte, Lorena Escudero Sanchez, Mireia Crispin-Ortuzar, Ramona Woitek, Cathal McCague, James D. Brenton, Ozan Öktem, Evis Sala, Leonardo Rundo

Comput. Biol. Medicine, September, 2023

Navigating the development challenges in creating complex data systems.

Sören Dittmer, Michael Roberts, Julian D. Gilbey, Ander Biguri, Ian Selby, Anna Breger, Matthew Thorpe, Jonathan R. Weir-McCall, Effrossyni Gkrania-Klotsas, Anna Korhonen, Emily R. Jefferson, Georg Langs, Guang Yang, Helmut Prosch, Jan Stanczuk, Jing Tang, Judith Babar, Lorena Escudero Sanchez, Philip Teare, Mishal Patel, Marcel Wassin, Markus Holzer, Nicholas Walton, Pietro Lió, Tolou Shadbahr, Evis Sala, Jacobus Preller, James H. F. Rudd, John A. D. Aston, Carola-Bibiane Schönlieb

Nat. Mac. Intell., July, 2023

2022

Author Correction: Advancing COVID-19 diagnosis with privacy-preserving collaboration in artificial intelligence.

Xiang Bai, Hanchen Wang, Liya Ma, Yongchao Xu, Jiefeng Gan, Ziwei Fan, Fan Yang, Ke Ma, Jiehua Yang, Song Bai, Chang Shu, Xinyu Zou, Renhao Huang, Changzheng Zhang, Xiaowu Liu, Dandan Tu, Chuou Xu, Wenqing Zhang, Xi Wang, Anguo Chen, Yu Zeng, Dehua Yang, Ming-Wei Wang, Nagaraj Holalkere, Neil J. Halin, Ihab R. Kamel, Jia Wu, Xuehua Peng, Xiang Wang, Jianbo Shao, Pattanasak Mongkolwat, Jianjun Zhang, Weiyang Liu, Michael Roberts, Zhongzhao Teng, Lucian Beer, Lorena Escudero Sanchez, Evis Sala, Daniel L. Rubin, Adrian Weller, Joan Lasenby, Chuansheng Zheng, Jianming Wang, Zhen Li, Carola Schönlieb, Tian Xia

Nat. Mach. Intell., 2022

Automated Segmentation of Computed Tomography Images with Submanifold Sparse Convolutional Networks.

Saúl Alonso-Monsalve, Leigh H. Whitehead, Adam Aurisano, Lorena Escudero Sanchez

CoRR, 2022

Calibrating Ensembles for Scalable Uncertainty Quantification in Deep Learning-based Medical Segmentation.

Thomas Buddenkotte, Lorena Escudero Sanchez, Mireia Crispin-Ortuzar, Ramona Woitek, Cathal McCague, James D. Brenton, Ozan Öktem, Evis Sala, Leonardo Rundo

CoRR, 2022

2021

Advancing COVID-19 diagnosis with privacy-preserving collaboration in artificial intelligence.

Xiang Bai, Hanchen Wang, Liya Ma, Yongchao Xu, Jiefeng Gan, Ziwei Fan, Fan Yang, Ke Ma, Jiehua Yang, Song Bai, Chang Shu, Xinyu Zou, Renhao Huang, Changzheng Zhang, Xiaowu Liu, Dandan Tu, Chuou Xu, Wenqing Zhang, Xi Wang, Anguo Chen, Yu Zeng, Dehua Yang, Ming-Wei Wang, Nagaraj Holalkere, Neil J. Halin, Ihab R. Kamel, Jia Wu, Xuehua Peng, Xiang Wang, Jianbo Shao, Pattanasak Mongkolwat, Jianjun Zhang, Weiyang Liu, Michael Roberts, Zhongzhao Teng, Lucian Beer, Lorena Escudero Sanchez, Evis Sala, Daniel L. Rubin, Adrian Weller, Joan Lasenby, Chuansheng Zheng, Jianming Wang, Zhen Li, Carola Schönlieb, Tian Xia

Nat. Mach. Intell., 2021

Advancing COVID-19 Diagnosis with Privacy-Preserving Collaboration in Artificial Intelligence.

Xiang Bai, Hanchen Wang, Liya Ma, Yongchao Xu, Jiefeng Gan, Ziwei Fan, Fan Yang, Ke Ma, Jiehua Yang, Song Bai, Chang Shu, Xinyu Zou, Renhao Huang, Changzheng Zhang, Xiaowu Liu, Dandan Tu, Chuou Xu, Wenqing Zhang, Xi Wang, Anguo Chen, Yu Zeng, Dehua Yang, Ming-Wei Wang, Nagaraj Holalkere, Neil J. Halin, Ihab R. Kamel, Jia Wu, Xuehua Peng, Xiang Wang, Jianbo Shao, Pattanasak Mongkolwat, Jianjun Zhang, Weiyang Liu, Michael Roberts, Zhongzhao Teng, Lucian Beer, Lorena Escudero Sanchez, Evis Sala, Daniel L. Rubin, Adrian Weller, Joan Lasenby, Chuangsheng Zheng, Jianming Wang, Zhen Li, Carola-Bibiane Schönlieb, Tian Xia

CoRR, 2021