Jeraj, Robert
University of Wisconsin–Madison
6 papers on CoChatORCID 0000-0002-2192-2931
Most cited papers
- Verified
A Randomized Trial of Bevacizumab for Newly Diagnosed Glioblastoma
Gilbert, M. R., Dignam, J. J., Armstrong, T. S., Wefel, J. S., Blumenthal, D. T., Vogelbaum, M. A., Colman, H., Chakravarti, A., Pugh, S., Won, M., et al. (2014) · New England Journal of Medicine
Glioma Diagnosis and TreatmentAngiogenesis and VEGF in Cancer
Cited by 2,834
- Verified
Federated learning enables big data for rare cancer boundary detection
Pati, S., Baid, U., Edwards, B., Sheller, M., Wang, S.-H., Reina, G. A., Foley, P., Gruzdev, A., Karkada, D., Davatzikos, C., et al. (2022) · Nature Communications
Privacy-Preserving Technologies in DataBrain Tumor Detection and Classification
Cited by 394
- Verified
Impact of the Definition of Peak Standardized Uptake Value on Quantification of Treatment Response
Vanderhoek, M., Perlman, S. B., & Jeraj, R. (2012) · Journal of Nuclear Medicine
Medical Imaging Techniques and ApplicationsRadiomics and Machine Learning in Medical Imaging
Cited by 188
- Verified
Interpretation and visualization techniques for deep learning models in medical imaging
Huff, D. T., Weisman, A. J., & Jeraj, R. (2021) · Physics in Medicine & Biology
Explainable Artificial Intelligence (XAI)Artificial Intelligence in Healthcare and Education
Cited by 172
- Verified
RTOG 0825: Phase III double-blind placebo-controlled trial evaluating bevacizumab (Bev) in patients (Pts) with newly diagnosed glioblastoma (GBM).
Gilbert, M. R., Dignam, J., Won, M., Blumenthal, D. T., Vogelbaum, M. A., Aldape, K. D., Colman, H., Chakravarti, A., Jeraj, R., Armstrong, T. S., et al. (2013) · Journal of Clinical Oncology
Glioma Diagnosis and TreatmentAngiogenesis and VEGF in Cancer
Cited by 70
- Verified
Impact of Different Standardized Uptake Value Measures on PET-Based Quantification of Treatment Response
Vanderhoek, M., Perlman, S. B., & Jeraj, R. (2013) · Journal of Nuclear Medicine
Medical Imaging Techniques and ApplicationsRadiomics and Machine Learning in Medical Imaging
Cited by 47
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