George Lee

Publications

De Leon, A., Lee, G., Shih, N., Elliott, R., Feldman, M., & Madabhushi, A. (2016). Evaluating stability of histomorphometric features across scanner and staining variations: prostate cancer diagnosis from whole slide images.. Journal of medical imaging (Bellingham, Wash.), 3 (4), 047502.
Madabhushi, A., & Lee, G. (2016). Image analysis and machine learning in digital pathology: Challenges and opportunities.. Medical image analysis, 33 , 170-5.
Lee, G., Romo Bucheli, D., & Madabhushi, A. (2016). Adaptive Dimensionality Reduction with Semi-Supervision (AdDReSS): Classifying Multi-Attribute Biomedical Data.. PloS one, 11 (7), e0159088.
Ginsburg, S., Lee, G., Karabalin, R., & Madabhushi, A. (2016). Feature Importance in Nonlinear Embeddings (FINE): Applications in Digital Pathology.. IEEE transactions on medical imaging, 35 (1), 76-88.
Veltri, R., Zhu, G., Lee, G., Karabalin, R., Madabhushi, A., & Cheng, C. (2015). Histomorphometry of Digital Pathology: Case Study in Prostate Cancer. FRONTIERS OF MEDICAL IMAGING.
Lee, G., Singanamalli, A., Wang, Z., Feldman, M., Master, S., Shih, N., Spangler, E., Rebbeck, T., Tomaszewski, J., & Madabhushi, A. (2015). Supervised multi-view canonical correlation analysis (sMVCCA): integrating histologic and proteomic features for predicting recurrent prostate cancer.. IEEE transactions on medical imaging, 34 (1), 284-97.
Lee, G., Sparks, R., Karabalin, R., Shih, N., Feldman, M., Spangler, E., Rebbeck, T., Tomaszewski, J., & Madabhushi, A. (2014). Co-occurring gland angularity in localized subgraphs: predicting biochemical recurrence in intermediate-risk prostate cancer patients.. PloS one, 9 (5), e97954.
Lee, G., Karabalin, R., Veltri, R., Epstein, J., Christudass, C., & Madabhushi, A. (2013). Cell orientation entropy (COrE): predicting biochemical recurrence from prostate cancer tissue microarrays.. Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention, 16 (Pt 3), 396-403.
Ginsburg, S., Karabalin, R., Lee, G., Basavanhally, A., & Madabhushi, A. (2013). Variable importance in nonlinear kernels (VINK): classification of digitized histopathology.. Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention, 16 (Pt 2), 238-45.
Golugula, A., Lee, G., Master, S., Feldman, M., Tomaszewski, J., Speicher, D., & Madabhushi, A. (2011). Supervised regularized canonical correlation analysis: integrating histologic and proteomic measurements for predicting biochemical recurrence following prostate surgery.. BMC bioinformatics, 12 , 483.
Madabhushi, A., Agner, S., Basavanhally, A., Doyle, S., & Lee, G. (2011). Computer-aided prognosis: predicting patient and disease outcome via quantitative fusion of multi-scale, multi-modal data.. Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society, 35 (7-8), 506-14.
Golugula, A., Lee, G., & Madabhushi, A. (2011). Evaluating feature selection strategies for high dimensional, small sample size datasets.. Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, 2011 , 949-52.
Golugula, A., Lee, G., Master, S., Feldman, M., Tomaszewski, J., & Madabhushi, A. (2011). Supervised regularized canonical correlation analysis: integrating histologic and proteomic data for predicting biochemical failures.. Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, 2011 , 6434-7.
Madabhushi, A., Doyle, S., Lee, G., Basavanhally, A., Monaco, J., Masters, S., Tomaszewski, J., & Feldman, M. (2010). Integrated diagnostics: a conceptual framework with examples.. Clinical chemistry and laboratory medicine, 48 (7), 989-98.
Lee, G., Rodriguez, C., & Madabhushi, A. (2008). Investigating the efficacy of nonlinear dimensionality reduction schemes in classifying gene and protein expression studies.. IEEE/ACM transactions on computational biology and bioinformatics, 5 (3), 368-84.