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Zan Klanecek

Showing results (1-10 of 8) with videos related to

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Physics in Medicine and Biology|May 16, 2025
Uncertainty quantification for deep learning-based metastatic lesion segmentation on whole body PET/CTBrayden Schott, Victor Santoro-Fernandes, Zan Klanecek, et al.
Radiology. Artificial Intelligence|September 3, 2025
Using Explainable AI to Characterize Features in the Mirai Mammographic Breast Cancer Risk Prediction ModelYao-Kuan Wang, Zan Klanecek, Tobias Wagner, et al.
Radiology and Oncology|September 4, 2023
Breast cancer risk assessment and risk distribution in 3,491 Slovenian women invited for screening at the age of 50; a population-based cross-sectional studyKatja Jarm, Vesna Zadnik, Mojca Birk, et al.
Journal of Medical Imaging (Bellingham, Wash.)|June 29, 2026
Illustration of transfer learning from breast cancer detection to risk prediction: adaptation to local data and local objectivesTobias Wagner, Zan Klanecek, Yao-Kuan Wang, et al.
Physics in Medicine and Biology|April 7, 2025
Sensitivity of a deep-learning-based breast cancer risk prediction modelZan Klanecek, Yao-Kuan Wang, Tobias Wagner, et al.
Physics in Medicine and Biology|February 6, 2025
Impact of pectoral muscle removal on deep-learning-based breast cancer risk predictionZan Klanecek, Yao-Kuan Wang, Tobias Wagner, et al.
Physics in Medicine and Biology|May 3, 2023
Uncertainty estimation for deep learning-based pectoral muscle segmentation via Monte Carlo dropoutZan Klanecek, Tobias Wagner, Yao-Kuan Wang, et al.
Physics in Medicine and Biology|December 11, 2024
Longitudinal interpretability of deep learning based breast cancer risk predictionZan Klanecek, Yao-Kuan Wang, Tobias Wagner, et al.
Pageof 1

Showing results (1-10 of 8) with videos related to

Sort By:
Pageof 1
Physics in Medicine and Biology|May 16, 2025
Uncertainty quantification for deep learning-based metastatic lesion segmentation on whole body PET/CTBrayden Schott, Victor Santoro-Fernandes, Zan Klanecek, et al.
Radiology. Artificial Intelligence|September 3, 2025
Using Explainable AI to Characterize Features in the Mirai Mammographic Breast Cancer Risk Prediction ModelYao-Kuan Wang, Zan Klanecek, Tobias Wagner, et al.
Radiology and Oncology|September 4, 2023
Breast cancer risk assessment and risk distribution in 3,491 Slovenian women invited for screening at the age of 50; a population-based cross-sectional studyKatja Jarm, Vesna Zadnik, Mojca Birk, et al.
Journal of Medical Imaging (Bellingham, Wash.)|June 29, 2026
Illustration of transfer learning from breast cancer detection to risk prediction: adaptation to local data and local objectivesTobias Wagner, Zan Klanecek, Yao-Kuan Wang, et al.
Physics in Medicine and Biology|April 7, 2025
Sensitivity of a deep-learning-based breast cancer risk prediction modelZan Klanecek, Yao-Kuan Wang, Tobias Wagner, et al.
Physics in Medicine and Biology|February 6, 2025
Impact of pectoral muscle removal on deep-learning-based breast cancer risk predictionZan Klanecek, Yao-Kuan Wang, Tobias Wagner, et al.
Physics in Medicine and Biology|May 3, 2023
Uncertainty estimation for deep learning-based pectoral muscle segmentation via Monte Carlo dropoutZan Klanecek, Tobias Wagner, Yao-Kuan Wang, et al.
Physics in Medicine and Biology|December 11, 2024
Longitudinal interpretability of deep learning based breast cancer risk predictionZan Klanecek, Yao-Kuan Wang, Tobias Wagner, et al.
Pageof 1