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Connection

Co-Authors

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

14.110
  1. Comparison of chest X-ray radiography AI model to comorbidities for predicting intensive care unit admission for COVID-19. J Med Imaging (Bellingham). 2026 Jul; 13(4):044501.
    View in: PubMed
    Score: 0.983
  2. Ethical Responsibility in the Off-Label Use of AI in Medical Imaging. J Clin Ethics. 2026; 37(2):130-134.
    View in: PubMed
    Score: 0.973
  3. 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: 0.929
  4. 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: 0.914
  5. 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: 0.902
  6. AI-based automated segmentation for ovarian/adnexal masses and their internal components on ultrasound imaging. J Med Imaging (Bellingham). 2024 Jul; 11(4):044505.
    View in: PubMed
    Score: 0.861
  7. 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: 0.806
  8. 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: 0.800
  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: 0.740
  10. Multi-Stage Harmonization for Robust AI across Breast MR Databases. Cancers (Basel). 2021 Sep 26; 13(19).
    View in: PubMed
    Score: 0.706
  11. 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: 0.694
  12. Harmonization of radiomic features of breast lesions across international DCE-MRI datasets. J Med Imaging (Bellingham). 2020 Jan; 7(1):012707.
    View in: PubMed
    Score: 0.634
  13. Comparison of Breast MRI Tumor Classification Using Human-Engineered Radiomics, Transfer Learning From Deep Convolutional Neural Networks, and Fusion Methods. Proc IEEE Inst Electr Electron Eng. 2020 Jan; 108(1):163-177.
    View in: PubMed
    Score: 0.621
  14. 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: 0.590
  15. 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: 0.559
  16. Task-Based Sampling of Patient Data for Rigorous Machine Learning/AI Performance Assessment. J Imaging Inform Med. 2026 Mar 10.
    View in: PubMed
    Score: 0.240
  17. Machine learning evaluation of pneumonia severity: subgroup performance in the Medical Imaging and Data Resource Center modified radiographic assessment of lung edema mastermind challenge. J Med Imaging (Bellingham). 2025 Sep; 12(5):054502.
    View in: PubMed
    Score: 0.233
  18. Demonstration of Interoperability Between MIDRC and N3C: A COVID-19 Severity Prediction Use Case. J Imaging Inform Med. 2026 Jun; 39(3):2062-2071.
    View in: PubMed
    Score: 0.231
  19. Multimodal data curation via interoperability: use cases with the Medical Imaging and Data Resource Center. Sci Data. 2025 08 01; 12(1):1340.
    View in: PubMed
    Score: 0.230
  20. 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: 0.205
  21. 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: 0.201
  22. Impact of continuous learning on diagnostic breast MRI AI: evaluation on an independent clinical dataset. J Med Imaging (Bellingham). 2022 May; 9(3):034502.
    View in: PubMed
    Score: 0.185
  23. Improved Classification of Benign and Malignant Breast Lesions Using Deep Feature Maximum Intensity Projection MRI in Breast Cancer Diagnosis Using Dynamic Contrast-enhanced MRI. Radiol Artif Intell. 2021 May; 3(3):e200159.
    View in: PubMed
    Score: 0.170
  24. Radiomics methodology for breast cancer diagnosis using multiparametric magnetic resonance imaging. J Med Imaging (Bellingham). 2020 Jul; 7(4):044502.
    View in: PubMed
    Score: 0.164
  25. A deep learning methodology for improved breast cancer diagnosis using multiparametric MRI. Sci Rep. 2020 06 29; 10(1):10536.
    View in: PubMed
    Score: 0.162
  26. Hybrid artificial intelligence echogenic components-based diagnosis of adnexal masses on ultrasound. Med Phys. 2025 Jul; 52(7):e17983.
    View in: PubMed
    Score: 0.057
  27. 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: 0.056
  28. Hybrid artificial intelligence echogenic components-based diagnosis of adnexal masses on ultrasound. ArXiv. 2025 Apr 16.
    View in: PubMed
    Score: 0.056
  29. Impact of retraining and data partitions on the generalizability of a deep learning model in the task of COVID-19 classification on chest radiographs. J Med Imaging (Bellingham). 2024 Nov; 11(6):064503.
    View in: PubMed
    Score: 0.055
  30. 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: 0.053
  31. 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: 0.049
  32. Differences in Molecular Subtype Reference Standards Impact AI-based Breast Cancer Classification with Dynamic Contrast-enhanced MRI. Radiology. 2023 04; 307(1):e220984.
    View in: PubMed
    Score: 0.048
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.