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Vamathevan, J., Clark, D., Czodrowski, P., Dunham, I., Ferran, E., Lee, G., Liu, B., Madabhushi, A., Shah, P., Spitzer, M., & Zhao, S.(2019).Applications of machine learning in drug discovery and development.Nature Reviews Drug Discovery,18(6),463-477.
Carleton, N., Lee, G., Madabhushi, A., & Veltri, R.(2018).Advances in the computational and molecular understanding of the prostate cancer cell nucleus: CARLETON et al..Journal of Cellular Biochemistry.
Chandramouli, S., Leo, P., Lee, G., Elliott, R., Zhu, G., Veltri, R., & Madabhushi, A.(2018).MP12-17 COMPUTER EXTRACTED FEATURES OF NUCLEI SHAPE, ARCHITECTURE AND ORIENTATION FROM INITIAL H&E TISSUE BIOPSIES PREDICT DISEASE PROGRESSION FOR PROSTATE CANCER PATIENTS ON ACTIVE SURVEILLANCE.The Journal of Urology,199(4),e142-e143.
Lee, G., Romo Bucheli, D., & Madabhushi, A.(2016).Adaptive Dimensionality Reduction with Semi-Supervision (AdDReSS): Classifying Multi-Attribute Biomedical Data.PLoS ONE [19326203],11(7).
Lee, G., Veltri, R., Zhu, G., Ali, S., Epstein, J., & Madabhushi, A.(2016).Nuclear Shape and Architecture in Benign Fields Predict Biochemical Recurrence in Prostate Cancer Patients Following Radical Prostatectomy: Preliminary Findings.European Urology Focus [24054569].
Madabhushi, A., & Lee, G.(2016).Image analysis and machine learning in digital pathology: Challenges and opportunities.Medical Image Analysis [13618415],33, 170-175.
Madabhushi, A., Ginsburg, S., & Lee, G.(2016).Feature Importance in Nonlinear Embeddings (FINE): Applications in Digital Pathology.IEEE Transactions on Medical Imaging,35(1),76 - 88.
Gawlik, A., Lee, G., Whitney, J., Epstein, J., Veltri, R., & Madabhushi, A.(2016).MP02-17 COMPUTER EXTRACTED NUCLEAR FEATURES FROM FEULGEN AND H&E IMAGES PREDICT BIOCHEMICAL RECURRENCE IN PROSTATE CANCER PATIENTS FOLLOWING RADICAL PROSTATECTOMY.The Journal of Urology [00225347],195(4),e16-e17.
