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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.
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
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.
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
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.
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., 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.
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.
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.
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.
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.
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
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.
Li, H., Bera, K., Gilmore, H., Zhang, Z., Cuzick, J., Thorat, M., & Madabhushi, A.(2020).Abstract P5-06-15: Computer extracted features of nuclear shape, orientation disorder and texture from H&E Whole slide images are associated with disease-free survival in ductal carcinoma in situ (DCIS).San Antonio Breast Cancer Symposium; San Antonio, Texas.