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Frontiers in Oncology|July 5, 2022
Clinically Interpretable Radiomics-Based Prediction of Histopathologic Response to Neoadjuvant Chemotherapy in High-Grade Serous Ovarian CarcinomaLeonardo Rundo, Lucian Beer, Lorena Escudero Sanchez, et al.
European Journal of Radiology Open|September 16, 2024
Using machine learning to predict carotid artery symptoms from CT angiography: A radiomics and deep learning approachElizabeth P V Le, Mark Y Z Wong, Leonardo Rundo, et al.
Scientific Reports|February 11, 2021
Assessing robustness of carotid artery CT angiography radiomics in the identification of culprit lesions in cerebrovascular eventsElizabeth P V Le, Leonardo Rundo, Jason M Tarkin, et al.
Nature Communications|October 24, 2023
Integrated radiogenomics models predict response to neoadjuvant chemotherapy in high grade serous ovarian cancerMireia Crispin-Ortuzar, Ramona Woitek, Marika A V Reinius, et al.
European Radiology Experimental|December 6, 2023
Deep learning-based segmentation of multisite disease in ovarian cancerThomas Buddenkotte, Leonardo Rundo, Ramona Woitek, et al.
Radiology. Imaging Cancer|August 18, 2020
Hyperpolarized 13C MRI of Tumor Metabolism Demonstrates Early Metabolic Response to Neoadjuvant Chemotherapy in Breast CancerRamona Woitek, Mary A McLean, Andrew B Gill, et al.
EJNMMI Research|April 17, 2025
Assessment of early response to neoadjuvant chemotherapy in multi-site high-grade serous ovarian cancer using hyperpolarized-13C MRILucian Beer, Vlad Bura, Stephan Ursprung, et al.
Cancer Research|October 9, 2021
Hyperpolarized Carbon-13 MRI for Early Response Assessment of Neoadjuvant Chemotherapy in Breast Cancer PatientsRamona Woitek, Mary A McLean, Stephan Ursprung, et al.
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