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Fredrik Strand

Showing results (41-50 of 57) with videos related to

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Radiology|September 8, 2020
Identification of Women at High Risk of Breast Cancer Who Need Supplemental ScreeningMikael Eriksson, Kamila Czene, Fredrik Strand, et al.
Nature Medicine|July 8, 2024
AI-based selection of individuals for supplemental MRI in population-based breast cancer screening: the randomized ScreenTrustMRI trialMattie Salim, Yue Liu, Moein Sorkhei, et al.
Medical Physics|January 31, 2019
Derived mammographic masking measures based on simulated lesions predict the risk of interval cancer after controlling for known risk factors: a case-case analysisBenjamin Hinton, Lin Ma, Amir Pasha Mahmoudzadeh, et al.
Radiology|October 24, 2023
Optimizing the Pairs of Radiologists That Double Read Screening MammogramsJessie J J Gommers, Craig K Abbey, Fredrik Strand, et al.
Medical Decision Making : an International Journal of the Society for Medical Decision Making|July 30, 2024
Modeling Radiologists' Assessments to Explore Pairing Strategies for Optimized Double Reading of Screening MammogramsJessie J J Gommers, Craig K Abbey, Fredrik Strand, et al.
Nature Medicine|January 14, 2022
Optimizing risk-based breast cancer screening policies with reinforcement learningAdam Yala, Peter G Mikhael, Constance Lehman, et al.
Tomography (Ann Arbor, Mich.)|June 18, 2020
Comparison of Segmentation Methods in Assessing Background Parenchymal Enhancement as a Biomarker for Response to Neoadjuvant TherapyAlex Anh-Tu Nguyen, Vignesh A Arasu, Fredrik Strand, et al.
Journal of Breast Imaging|August 18, 2020
Predictive Value of Breast MRI Background Parenchymal Enhancement for Neoadjuvant Treatment Response among HER2- PatientsVignesh A Arasu, Paul Kim, Wen Li, et al.
Radiology|May 23, 2023
Standalone AI for Breast Cancer Detection at Screening Digital Mammography and Digital Breast Tomosynthesis: A Systematic Review and Meta-AnalysisJung Hyun Yoon, Fredrik Strand, Pascal A T Baltzer, et al.
NPJ Precision Oncology|December 4, 2025
Collaborative framework on responsible AI in LLM-driven CDSS for precision oncology leveraging real-world patient dataSonja Mathes, Dyke Ferber, Tobias Dreyer, et al.
Pageof 6

Showing results (41-50 of 57) with videos related to

Sort By:
Pageof 6
Radiology|September 8, 2020
Identification of Women at High Risk of Breast Cancer Who Need Supplemental ScreeningMikael Eriksson, Kamila Czene, Fredrik Strand, et al.
Nature Medicine|July 8, 2024
AI-based selection of individuals for supplemental MRI in population-based breast cancer screening: the randomized ScreenTrustMRI trialMattie Salim, Yue Liu, Moein Sorkhei, et al.
Medical Physics|January 31, 2019
Derived mammographic masking measures based on simulated lesions predict the risk of interval cancer after controlling for known risk factors: a case-case analysisBenjamin Hinton, Lin Ma, Amir Pasha Mahmoudzadeh, et al.
Radiology|October 24, 2023
Optimizing the Pairs of Radiologists That Double Read Screening MammogramsJessie J J Gommers, Craig K Abbey, Fredrik Strand, et al.
Medical Decision Making : an International Journal of the Society for Medical Decision Making|July 30, 2024
Modeling Radiologists' Assessments to Explore Pairing Strategies for Optimized Double Reading of Screening MammogramsJessie J J Gommers, Craig K Abbey, Fredrik Strand, et al.
Nature Medicine|January 14, 2022
Optimizing risk-based breast cancer screening policies with reinforcement learningAdam Yala, Peter G Mikhael, Constance Lehman, et al.
Tomography (Ann Arbor, Mich.)|June 18, 2020
Comparison of Segmentation Methods in Assessing Background Parenchymal Enhancement as a Biomarker for Response to Neoadjuvant TherapyAlex Anh-Tu Nguyen, Vignesh A Arasu, Fredrik Strand, et al.
Journal of Breast Imaging|August 18, 2020
Predictive Value of Breast MRI Background Parenchymal Enhancement for Neoadjuvant Treatment Response among HER2- PatientsVignesh A Arasu, Paul Kim, Wen Li, et al.
Radiology|May 23, 2023
Standalone AI for Breast Cancer Detection at Screening Digital Mammography and Digital Breast Tomosynthesis: A Systematic Review and Meta-AnalysisJung Hyun Yoon, Fredrik Strand, Pascal A T Baltzer, et al.
NPJ Precision Oncology|December 4, 2025
Collaborative framework on responsible AI in LLM-driven CDSS for precision oncology leveraging real-world patient dataSonja Mathes, Dyke Ferber, Tobias Dreyer, et al.
Pageof 6