Shiradkar, R., Mahran, A., Sharma, S., Conroy, B., Tirumani, S., Ponsky, L., & Madabhushi, A.(2020).MP81-06 RADIOMIC FEATURES OF PROSTATE CANCER PATIENTS (GLEASON GRADE GROUP = 2) SHOW DIFFERENCES BETWEEN AFRICAN AMERICAN AND CAUCASIAN POPULATIONS ON BI-PARAMETRIC MRI: PRELIMINARY FINDINGS.The Journal of Urology,203
Gui, J., Li, D., Chen, Z., Rhee, J., Xiao, X., Zhang, M., Jee, K., Li, Z., & Chen, H.(2020).APTrace: A Responsive System for Agile Enterprise Level Causality Analysis.IEEE.
Guo, Y., Liu, F., Wang, A., & Liu, C.(2020).AccuPIPE: Accurate Heavy Flow Detection in the Data Plane Using Programmable Switches.IEEE/IFIP Network Operations and Management Symposium.
Leo, P., Elliott, R., Janowczyk, A., Janaki, N., Bera, K., Shiradkar, R., El-Fahmawi, A., Kim, J., Shahait, M., Shah, A., Thulasidass, H., Tewari, A., Gupta, S., Shih, N., Feldman, M., Lal, P., Lee, D., & Madabhushi, A.(2020).PD52-02 COMPUTER-EXTRACTED FEATURES OF GLAND MORPHOLOGY FROM DIGITAL TISSUE IMAGES IS COMPARABLE TO DECIPHER FOR PROGNOSIS OF BIOCHEMICAL RECURRENCE RISK POST-SURGERY.The Journal of Urology,203, e1089-e1090.
Gao, P., Xiao, X., Li, D., Jee, K., Chen, H., Kulkarni, S., & Mittal, P.(2020).Querying Streaming System Monitoring Data for Enterprise System Anomaly Detection.IEEE.
Hiremath, A., Shiradkar, R., Merisaari, H., Li, L., Prasanna, P., Ettala, O., Taimen, P., Aronen, H., Boström, P., Pierce, J., Tirumani, S., Rastinehad, A., Jambor, I., Purysko, A., & Madabhushi, A.(2020).PD57-05 A DEEP LEARNING NETWORK ALONG WITH PIRADS CAN DISTINGUISH CLINICALLY SIGNIFICANT AND INSIGNIFICANT PROSTATE CANCER ON BI-PARAMETRIC MRI: A MULTI-CENTER STUDY.The Journal of Urology,203
Tackett, S., Guo, F., Clifford, C., Campanaro, C., Nethery, D., Horton, K., Fletcher, D., Hsieh, Y., Bonfield, T., Loparo, K. A., Dick, T. A., & Jacono, F. A.(2020).Translational Study Tracking Dynamic Changes in Cardiac Pattern Variability and Systemic Inflammation in Critically Ill Patients.The FASEB Journal,34(S1),1-1.
Shiradkar, R., Zuo, R., Mahran, A., Ponsky, L., Tirumani, S., & Madabhushi, A.(2020).Radiomic features derived from periprostatic fat on pre-surgical T2w MRI predict extraprostatic extension of prostate cancer identified on post-surgical pathology: preliminary results.Medical Imaging: Computer-Aided Diagnosis.
Hiremath, A., Shiradkar, R., Braman, N., Prasanna, P., Rastinehad, A., Purysko, A., & Madabhushi, A.(2020).A combination of intra- and peri-tumoral deep features from prostate bi-parametric MRI can distinguish clinically significant and insignificant prostate cancer.Medical Imaging: Computer-Aided Diagnosis.
Azarianpour Esfahani, S., Corredor-Prada, G., Bera, K., Leo, P., Braman, N., Fu, P., Mahdi, H., & Madabhushi, A.(2020).Computer extracted features related to the spatial arrangement of tumor-infiltrating lymphocytes predict overall survival in epithelial ovarian cancer.Medical Imaging: Digital Pathology.
Ding, R., Prasanna, P., Corredor-Prada, G., Lu, C., Velu, P., Le, K., Leo, P., Beig, N., Velcheti, V., Rimm, D., Schalper, K., & Madabhushi, A.(2020).Compactness measures of tumor infiltrating lymphocytes in lung adenocarcinoma are associated with overall patient survival and immune scores.Medical Imaging: Digital Pathology.
Selvam, A., Antunes, J., Bera, K., Ofshteyn, A., Brady, J., Bingmer, K., Friedman, K., Stein, S., Paspulati, R., Purysko, A., Kalady, M., Madabhushi, A., & Viswanath, S.(2020).Multi-site evaluation of stable radiomic features for more accurate evaluation of pathologic downstaging on MRI after chemoradiation for rectal cancers.Medical Imaging: Computer-Aided Diagnosis.
Liu, C., Zhou, C., Wang, J., Fietkiewicz, C., & Loparo, K. A.(2020).The role of coupling connections in a model of the cortico-basal ganglia-thalamocortical neural loop for the generation of beta oscillations.Neural Networks,123, 381-392.
Strezoski, L., Dumnic, B., Popadic, B., Prica, M., & Loparo, K. A.(2020).Novel Fault Models for Electronically Coupled Distributed Energy Resources and their Laboratory Validation.IEEE Transactions on Power Systems,35(2),1209-1217.
Mohseni, P.(2020).A 1–10MHz frequency-aware CMOS active rectifier with dual-loop adaptive delay compensation and >230mW output power for capacitively powered biomedical implants.IEEE J. Solid-State Circuits,55(3),756-766.
Vaidya, P., Bera, K., Gupta, A., WAng, X., Corredor-Prada, G., Fu, P., Beig, N., Prasanna, P., Patil, P., Velu, P., Rajiah, P., Gilkeson, R., Feldman, M., Choi, H., Velcheti, V., & Madabhushi, A.(2020).CT derived radiomic score for predicting the added benefit of adjuvant chemotherapy following surgery in stage I, II resectable non-small cell lung cancer: a retrospective multicohort study for outcome prediction.The Lancet Digital Health,2(3),e116-e128.
Erfani, R., Marefat, F., Nag, S., & Mohseni, P.(2020).A 1-10-MHz Frequency-Aware CMOS Active Rectifier With Dual-Loop Adaptive Delay Compensation and >230-mW Output Power for Capacitively Powered Biomedical Implants.IEEE Journal of Solid-State Circuits,55(3),756-766.
Sandulache, V., Lei, Y., Heasley, L., Chang, M., Amos, C., Sturgis, E., Graboyes, E., Chiao, E., Rogus-Pulia, N., Lewis, S., Madabhushi, A., Frederick, M., Sabichi, A., Ittmann, M., Yarbrough, W., Chung, C., Ferrarotto, R., Mai, W., Skinner, H., Duvvuri, U., Gerngross, P., & Sikora, A.(2020).Innovations in risk-stratification and treatment of Veterans with oropharynx cancer; roadmap of the 2019 Field Based Meeting.Oral Oncology,102
Braman, N., Adoui, M., Vulchi, M., Turk, P., Etesami, M., Fu, P., Drisis, S., Varadan, V., Plecha, D., Benjelloun, M., Abraham, J., & Madabhushi, A.(2020).Abstract P4-10-13: Validation of neural network approach for the prediction of HER2-targeted neoadjuvant chemotherapy response from pretreatment MRI: A multi-site study.San Antonio Breast Cancer Symposium; San Antonio, Texas.
