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One or more keywords matched the following properties of Whitney, Heather
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overview Heather M. Whitney, PhD is a research assistant professor in the Department of Radiology at the University of Chicago. Dr. Whitney received a Master of Science in Medical Physics from the Vanderbilt University School of Medicine and Master of Science and PhD in Physics from Vanderbilt University. While at Vanderbilt, she trained and conducted research at the Vanderbilt University Institute of Imaging Science with John Gore as her advisor, and additionally collaborated with faculty in the Department of Radiation Oncology. Before coming to the University of Chicago, she was a tenured professor of physics at a small liberal arts college, where she fostered an NIH-funded research program in medical physics in collaboration with faculty in Radiology at the University of Chicago. At the University of Chicago, she conducts research in computer-aided diagnosis of breast and ovarian cancer, focusing on the modalities of dynamic contrast-enhanced magnetic resonance imaging and ultrasound. Her primary areas of interest are in artificial intelligence and radiomics across the imaging and classification pipeline, from image acquisition to performance evaluation and data harmonization. She also conducts research and collaborates in MIDRC, the Medical Imaging and Data Resource Center. Within MIDRC she works on methods of task-based distributions, interoperability between data enclaves, and monitoring and studying the diversity and representativeness of the MIDRC data commons to foster research in AI and health disparities.
One or more keywords matched the following items that are connected to Whitney, Heather
Item TypeName
Concept Image Interpretation, Computer-Assisted
Concept Phantoms, Imaging
Concept Magnetic Resonance Imaging
Academic Article Additive Benefit of Radiomics Over Size Alone in the Distinction Between Benign Lesions and Luminal A Cancers on a Large Clinical Breast MRI Dataset.
Academic Article Harmonization of radiomic features of breast lesions across international DCE-MRI datasets.
Academic Article A deep learning methodology for improved breast cancer diagnosis using multiparametric MRI.
Academic Article Radiomics methodology for breast cancer diagnosis using multiparametric magnetic resonance imaging.
Academic Article Robustness of radiomic features of benign breast lesions and hormone receptor positive/HER2-negative cancers across DCE-MR magnet strengths.
Academic Article Performance metric curve analysis framework to assess impact of the decision variable threshold, disease prevalence, and dataset variability in two-class classification.
Academic Article Impact of continuous learning on diagnostic breast MRI AI: evaluation on an independent clinical dataset.
Academic Article Optimization of MAGIC gel formulation for three-dimensional radiation therapy dosimetry.
Academic Article Accuracy and robustness of a simple algorithm to measure vessel diameter from B-mode ultrasound images.
Academic Article Effect of biopsy on the MRI radiomics classification of benign lesions and luminal A cancers.
Academic Article Differences in Molecular Subtype Reference Standards Impact AI-based Breast Cancer Classification with Dynamic Contrast-enhanced MRI.
Grant Assessment of Repeatability and Robustness of Radiomics in Breast Cancer Imaging
Academic Article Toward fairness in artificial intelligence for medical image analysis: identification and mitigation of potential biases in the roadmap from data collection to model deployment.
Academic Article Longitudinal assessment of demographic representativeness in the Medical Imaging and Data Resource Center open data commons.
Academic Article Predicting intensive care need for COVID-19 patients using deep learning on chest radiography.
Academic Article Role of sureness in evaluating AI/CADx: Lesion-based repeatability of machine learning classification performance on breast MRI.
Academic Article Sequestration of imaging studies in MIDRC: stratified sampling to balance demographic characteristics of patients in a multi-institutional data commons.
Academic Article Special Section Guest Editorial: Global Health, Bias, and Diversity in AI in Medical Imaging.
Academic Article MIDRC-MetricTree: a decision tree-based tool for recommending performance metrics in artificial intelligence-assisted medical image analysis.
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