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Cathal McCague
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2020 – today
- 2024
- [c1]Inês Prata Machado, Anna Reithmeir, Fryderyk Victor Kögl, Leonardo Rundo, Gabriel Funingana, Marika Reinius, Gift Mungmeeprued, Zeyu Gao, Cathal McCague, Eric Kerfoot, Ramona Woitek, Evis Sala, Yangming Ou, James D. Brenton, Julia A. Schnabel, Mireia Crispin:
A Self-supervised Image Registration Approach for Measuring Local Response Patterns in Metastatic Ovarian Cancer. WBIR 2024: 295-307 - [i3]Inês Prata Machado, Anna Reithmeir, Fryderyk Victor Kögl, Leonardo Rundo, Gabriel Funingana, Marika Reinius, Gift Mungmeeprued, Zeyu Gao, Cathal McCague, Eric Kerfoot, Ramona Woitek, Evis Sala, Yangming Ou, James D. Brenton, Julia A. Schnabel, Mireia Crispin:
A Self-Supervised Image Registration Approach for Measuring Local Response Patterns in Metastatic Ovarian Cancer. CoRR abs/2407.17114 (2024) - 2023
- [j2]Thomas Buddenkotte
, Lorena Escudero Sanchez
Calibrating ensembles for scalable uncertainty quantification in deep learning-based medical image segmentation. Comput. Biol. Medicine 163: 107096 (2023) - 2022
- [i2]Thomas Buddenkotte, Lorena Escudero Sanchez, Mireia Crispin-Ortuzar, Ramona Woitek, Cathal McCague
Calibrating Ensembles for Scalable Uncertainty Quantification in Deep Learning-based Medical Segmentation. CoRR abs/2209.09563 (2022) - 2021
- [j1]Michael Roberts
Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans. Nat. Mach. Intell. 3(3): 199-217 (2021) - 2020
- [i1]Michael Roberts
Machine learning for COVID-19 detection and prognostication using chest radiographs and CT scans: a systematic methodological review. CoRR abs/2008.06388 (2020)
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last updated on 2024-11-04 20:46 CET by the dblp team
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