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Connection

Co-Authors

This is a "connection" page, showing publications co-authored by Karen Drukker and Heather Whitney.
Connection Strength

2.617
  1. Introduction to the JMI Special Issue on Advances in Breast Imaging. J Med Imaging (Bellingham). 2025 Nov; 12(Suppl 2):S22001.
    View in: PubMed
    Score: 0.240
  2. Demonstration of Interoperability Between MIDRC and N3C: A COVID-19 Severity Prediction Use Case. J Imaging Inform Med. 2025 Aug 14.
    View in: PubMed
    Score: 0.239
  3. Sureness of classification of breast cancers as pure ductal carcinoma in situ or with invasive components on dynamic contrast-enhanced magnetic resonance imaging: application of likelihood assurance metrics for computer-aided diagnosis. J Med Imaging (Bellingham). 2025 Nov; 12(Suppl 2):S22012.
    View in: PubMed
    Score: 0.236
  4. AI analysis of medical images at scale as a health disparities probe: a feasibility demonstration using chest radiographs. ArXiv. 2025 Apr 08.
    View in: PubMed
    Score: 0.233
  5. MIDRC-MetricTree: a decision tree-based tool for recommending performance metrics in artificial intelligence-assisted medical image analysis. J Med Imaging (Bellingham). 2024 Mar; 11(2):024504.
    View in: PubMed
    Score: 0.217
  6. Role of sureness in evaluating AI/CADx: Lesion-based repeatability of machine learning classification performance on breast MRI. Med Phys. 2024 Mar; 51(3):1812-1821.
    View in: PubMed
    Score: 0.208
  7. Longitudinal assessment of demographic representativeness in the Medical Imaging and Data Resource Center open data commons. J Med Imaging (Bellingham). 2023 Nov; 10(6):61105.
    View in: PubMed
    Score: 0.207
  8. Toward fairness in artificial intelligence for medical image analysis: identification and mitigation of potential biases in the roadmap from data collection to model deployment. J Med Imaging (Bellingham). 2023 Nov; 10(6):061104.
    View in: PubMed
    Score: 0.204
  9. Performance metric curve analysis framework to assess impact of the decision variable threshold, disease prevalence, and dataset variability in two-class classification. J Med Imaging (Bellingham). 2022 May; 9(3):035502.
    View in: PubMed
    Score: 0.191
  10. Robustness of radiomic features of benign breast lesions and hormone receptor positive/HER2-negative cancers across DCE-MR magnet strengths. Magn Reson Imaging. 2021 10; 82:111-121.
    View in: PubMed
    Score: 0.179
  11. Effect of biopsy on the MRI radiomics classification of benign lesions and luminal A cancers. J Med Imaging (Bellingham). 2019 Jul; 6(3):031408.
    View in: PubMed
    Score: 0.152
  12. Additive Benefit of Radiomics Over Size Alone in the Distinction Between Benign Lesions and Luminal A Cancers on a Large Clinical Breast MRI Dataset. Acad Radiol. 2019 02; 26(2):202-209.
    View in: PubMed
    Score: 0.144
  13. MIDRC mRALE Mastermind Grand Challenge: AI to predict COVID severity on chest radiographs. J Med Imaging (Bellingham). 2025 Mar; 12(2):024505.
    View in: PubMed
    Score: 0.058
  14. Sequestration of imaging studies in MIDRC: stratified sampling to balance demographic characteristics of patients in a multi-institutional data commons. J Med Imaging (Bellingham). 2023 Nov; 10(6):064501.
    View in: PubMed
    Score: 0.053
  15. Predicting intensive care need for COVID-19 patients using deep learning on chest radiography. J Med Imaging (Bellingham). 2023 Jul; 10(4):044504.
    View in: PubMed
    Score: 0.052
Connection Strength

The connection strength for concepts is the sum of the scores for each matching publication.

Publication scores are based on many factors, including how long ago they were written and whether the person is a first or senior author.