Natalie Baughan

Affiliations: 
University of Chicago, Chicago, IL 
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Drukker K, Sahiner B, Hu T, et al. (2024) MIDRC-MetricTree: a decision tree-based tool for recommending performance metrics in artificial intelligence-assisted medical image analysis. Journal of Medical Imaging (Bellingham, Wash.). 11: 024504
Baughan N, Douglas L, Giger ML. (2024) Past, Present, and Future of Machine Learning and Artificial Intelligence for Breast Cancer Screening. Journal of Breast Imaging. 4: 451-459
Baughan N, Whitney HM, Drukker K, et al. (2023) Sequestration of imaging studies in MIDRC: stratified sampling to balance demographic characteristics of patients in a multi-institutional data commons. Journal of Medical Imaging (Bellingham, Wash.). 10: 064501
Whitney HM, Baughan N, Myers KJ, et al. (2023) Longitudinal assessment of demographic representativeness in the Medical Imaging and Data Resource Center open data commons. Journal of Medical Imaging (Bellingham, Wash.). 10: 61105
Baughan N, Li H, Lan L, et al. (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 effect. Journal of Medical Imaging (Bellingham, Wash.). 10: 044501
Li H, Robinson K, Lan L, et al. (2023) Temporal Machine Learning Analysis of Prior Mammograms for Breast Cancer Risk Prediction. Cancers. 15
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