Heather M. Whitney
Orcid: 0000-0002-7258-1102
According to our database1,
Heather M. Whitney
authored at least 17 papers
between 2018 and 2023.
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Bibliography
2023
Investigation of demographic implicit discrimination and disparate impact in chest radiography image-based AI for COVID-19 severity prediction.
Proceedings of the Medical Imaging 2023: Image Perception, 2023
Assistance tools for the evaluation of machine learning algorithm performance: the decision tree-based tools developed by the Medical Imaging and Data Resource Center (MIDRC) Technology Development Project (TDP) 3c effort.
Proceedings of the Medical Imaging 2023: Image Perception, 2023
2022
Case-based repeatability and operating point variability of AI: breast lesion classification based on deep transfer learning.
Proceedings of the Medical Imaging 2022: Image Perception, 2022
Proceedings of the Medical Imaging 2022: Image Perception, 2022
Effect of different molecular subtype reference standards in AI training: implications for DCE-MRI radiomics of breast cancers.
Proceedings of the Medical Imaging 2022: Computer-Aided Diagnosis, 2022
2021
Comparison of diagnostic performances, case-based repeatability, and operating sensitivity and specificity in classification of breast lesions using DCE-MRI.
Proceedings of the Medical Imaging 2021: Image Perception, 2021
Case-based diagnostic classification repeatability using radiomic features extracted from full-field digital mammography images of breast lesions.
Proceedings of the Medical Imaging 2021: Computer-Aided Diagnosis, 2021
2020
Comparison of Breast MRI Tumor Classification Using Human-Engineered Radiomics, Transfer Learning From Deep Convolutional Neural Networks, and Fusion Method.
Proc. IEEE, 2020
Repeatability profiles towards consistent sensitivity and specificity levels for machine learning on breast DCE-MRI.
Proceedings of the Medical Imaging 2020: Image Perception, 2020
Improvement of classification performance using harmonization across field strength of radiomic features extracted from DCE-MR images of the breast.
Proceedings of the Medical Imaging 2020: Computer-Aided Diagnosis, 2020
Case-based repeatability of machine learning classification performance on breast MRI.
Proceedings of the Medical Imaging 2020: Computer-Aided Diagnosis, 2020
Using ResNet feature extraction in computer-aided diagnosis of breast cancer on 927 lesions imaged with multiparametric MRI.
Proceedings of the Medical Imaging 2020: Computer-Aided Diagnosis, 2020
2019
Transfer Learning in 4D for Breast Cancer Diagnosis using Dynamic Contrast-Enhanced Magnetic Resonance Imaging.
CoRR, 2019
Effect of diversity of patient population and acquisition systems on the use of radiomics and machine learning for classification of 2, 397 breast lesions.
Proceedings of the Medical Imaging 2019: Computer-Aided Diagnosis, 2019
Radiomics and deep learning of diffusion-weighted MRI in the diagnosis of breast cancer.
Proceedings of the Medical Imaging 2019: Computer-Aided Diagnosis, 2019
2018
Robustness of radiomic breast features of benign lesions and luminal A cancers across MR magnet strengths.
Proceedings of the Medical Imaging 2018: Computer-Aided Diagnosis, 2018
Effect of biopsy on the MRI radiomics classification of benign lesions and luminal A cancers.
Proceedings of the 14th International Workshop on Breast Imaging, 2018