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Natalie Baughan

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

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Journal of Breast Imaging|February 28, 2024
Past, Present, and Future of Machine Learning and Artificial Intelligence for Breast Cancer ScreeningNatalie Baughan, Lindsay Douglas, Maryellen L Giger
Journal of Medical Imaging (Bellingham, Wash.)|July 10, 2023
Radiomic and deep learning characterization of breast parenchyma on full field digital mammograms and specimen radiographs: a pilot study of a potential cancer field effectNatalie Baughan, Hui Li, Li Lan, et al.
Journal of Imaging Informatics in Medicine|March 10, 2026
Task-Based Sampling of Patient Data for Rigorous Machine Learning/AI Performance AssessmentNatalie Baughan, Heather M Whitney, Karen Drukker, et al.
Journal of Medical Imaging (Bellingham, Wash.)|April 5, 2024
MIDRC-MetricTree: a decision tree-based tool for recommending performance metrics in artificial intelligence-assisted medical image analysisKaren Drukker, Berkman Sahiner, Tingting Hu, et al.
Journal of Medical Imaging (Bellingham, Wash.)|December 11, 2023
Sequestration of imaging studies in MIDRC: stratified sampling to balance demographic characteristics of patients in a multi-institutional data commonsNatalie Baughan, Heather M Whitney, Karen Drukker, et al.
Cancers|April 13, 2023
Temporal Machine Learning Analysis of Prior Mammograms for Breast Cancer Risk PredictionHui Li, Kayla Robinson, Li Lan, et al.
Journal of Medical Imaging (Bellingham, Wash.)|July 20, 2023
Longitudinal assessment of demographic representativeness in the Medical Imaging and Data Resource Center open data commonsHeather M Whitney, Natalie Baughan, Kyle J Myers, et al.
Journal of Medical Imaging (Bellingham, Wash.)|April 25, 2025
MIDRC mRALE Mastermind Grand Challenge: AI to predict COVID severity on chest radiographsSamuel G Armato, Karen Drukker, Lubomir Hadjiiski, et al.
Pageof 1

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

Sort By:
Pageof 1
Journal of Breast Imaging|February 28, 2024
Past, Present, and Future of Machine Learning and Artificial Intelligence for Breast Cancer ScreeningNatalie Baughan, Lindsay Douglas, Maryellen L Giger
Journal of Medical Imaging (Bellingham, Wash.)|July 10, 2023
Radiomic and deep learning characterization of breast parenchyma on full field digital mammograms and specimen radiographs: a pilot study of a potential cancer field effectNatalie Baughan, Hui Li, Li Lan, et al.
Journal of Imaging Informatics in Medicine|March 10, 2026
Task-Based Sampling of Patient Data for Rigorous Machine Learning/AI Performance AssessmentNatalie Baughan, Heather M Whitney, Karen Drukker, et al.
Journal of Medical Imaging (Bellingham, Wash.)|April 5, 2024
MIDRC-MetricTree: a decision tree-based tool for recommending performance metrics in artificial intelligence-assisted medical image analysisKaren Drukker, Berkman Sahiner, Tingting Hu, et al.
Journal of Medical Imaging (Bellingham, Wash.)|December 11, 2023
Sequestration of imaging studies in MIDRC: stratified sampling to balance demographic characteristics of patients in a multi-institutional data commonsNatalie Baughan, Heather M Whitney, Karen Drukker, et al.
Cancers|April 13, 2023
Temporal Machine Learning Analysis of Prior Mammograms for Breast Cancer Risk PredictionHui Li, Kayla Robinson, Li Lan, et al.
Journal of Medical Imaging (Bellingham, Wash.)|July 20, 2023
Longitudinal assessment of demographic representativeness in the Medical Imaging and Data Resource Center open data commonsHeather M Whitney, Natalie Baughan, Kyle J Myers, et al.
Journal of Medical Imaging (Bellingham, Wash.)|April 25, 2025
MIDRC mRALE Mastermind Grand Challenge: AI to predict COVID severity on chest radiographsSamuel G Armato, Karen Drukker, Lubomir Hadjiiski, et al.
Pageof 1