Electrical, Computer, and Systems Engineering Publications

Sunday, July 1, 2018

Make Evasion Harder: An Intelligent Android Malware Detection System

Hou, S., Ye, F., Song, Y., & Abdulhayoglu, M. (2018). Make Evasion Harder: An Intelligent Android Malware Detection System. International Joint Conferences on Artificial Intelligence Organization, ().

Friday, June 29, 2018

Nuclear shape and orientation features from H&E images predict survival in early-stage estrogen receptor-positive breast cancers

Lu, C., Romo-Bucheli, D., WAng, X., Janowczyk, A., Ganesan, S., Gilmore, H., ... Madabhushi, A. (2018). Nuclear shape and orientation features from H&E images predict survival in early-stage estrogen receptor-positive breast cancers. Laboratory Investigation, ().

Wednesday, June 20, 2018

Advances in the computational and molecular understanding of the prostate cancer cell nucleus: CARLETON et al.

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, ().

Tuesday, June 19, 2018

Periodicity: A Characteristic of Heart Rate Variability Modified by the Type of Mechanical Ventilation After Acute Lung Injury

Thungtong, A., Knoch, M., Jacono, F., Dick, T., & Loparo, K. A. (2018). Periodicity: A Characteristic of Heart Rate Variability Modified by the Type of Mechanical Ventilation After Acute Lung Injury. Frontiers in Physiology, 9 ().

Wednesday, June 6, 2018

Wind farm cooperative control for optimal power generation

Wang, F., & Garcia-Sanz, M. (2018). Wind farm cooperative control for optimal power generation. Wind Engineering, ().

Friday, June 1, 2018

Global Stabilization of a Class of Time-Delay Nonlinear Systems with Unknown Control Directions by Nonsmooth Feedback

Rattanamongkhonkun, K., Pongvuthithum, R., & Lin, W. (2018). Global Stabilization of a Class of Time-Delay Nonlinear Systems with Unknown Control Directions by Nonsmooth Feedback. IFAC-PapersOnLine (Proc. of the 14th IFAC Workshop on Time Delay Systems, June 28-30, 2018), 51 (14), 78-83.

Friday, June 1, 2018

Cross-Domain Sentiment Classification via A Bifurcation-LSTM

Ji, J., Luo, C., Chen, X., Yu, L., & Li, P. (2018). Cross-Domain Sentiment Classification via A Bifurcation-LSTM. Proceeding of the 22nd Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD'18), ().

Friday, June 1, 2018

A compressive sensing framework for high-site-density brain dopamine recording with fast-scan cyclic voltammetry

Mohseni, P. (2018). A compressive sensing framework for high-site-density brain dopamine recording with fast-scan cyclic voltammetry. 43rd Neural Interfaces Conf. (NIC), ().

Friday, June 1, 2018

Capacitive wireless power transfer (C–WPT) to neural implants

Mohseni, P. (2018). Capacitive wireless power transfer (C–WPT) to neural implants. 43rd Neural Interfaces Conf. (NIC), ().

Friday, June 1, 2018

An FPGA-based Flexible and MIMO-capable GPR System

Srivastav, A., Ariando, D., & Mandal, S. (2018). An FPGA-based Flexible and MIMO-capable GPR System. , (), 6-Jan.

Friday, June 1, 2018

Adaptive Regulation of Hypersonic Vehicle Systems with Partial Nonlinear Parametrization

Yang, S., Tao, G., Zhang, Y., & Lin, W. (2018). Adaptive Regulation of Hypersonic Vehicle Systems with Partial Nonlinear Parametrization. Proc. of American Control Conference (2018), (), 2527-2532.

Wednesday, May 30, 2018

Quantitative nuclear histomorphometry predicts oncotype DX risk categories for early stage ER+ breast cancer

Whitney, J., Corredor-Prada, G., Janowczyk, A., Ganesan, S., Doyle, S., Tomaszewski, J., ... Madabhushi, A. (2018). Quantitative nuclear histomorphometry predicts oncotype DX risk categories for early stage ER+ breast cancer. BMC Cancer, 18 (1).

Thursday, May 24, 2018

High-throughput adaptive sampling for whole-slide histopathology image analysis (HASHI) via convolutional neural networks: Application to invasive breast cancer detection

Cruz-Roa, A., Gilmore, H., Basavanhally, A., Feldman, M., Ganesan, S., Shih, N., ... Gonz�lez, F. (2018). High-throughput adaptive sampling for whole-slide histopathology image analysis (HASHI) via convolutional neural networks: Application to invasive breast cancer detection. PLoS ONE, 13 (5).

Wednesday, May 23, 2018

Novel Quantitative Imaging for Predicting Response to Therapy: Techniques and Clinical Applications

Bera, K., Velcheti, V., & Madabhushi, A. (2018). Novel Quantitative Imaging for Predicting Response to Therapy: Techniques and Clinical Applications. American Society of Clinical Oncology Educational Book, (38), 1008-1018.

Sunday, May 20, 2018

Combination of CT derived radiomic features and lymphovascular invasion status to predict disease recurrence following trimodality therapy in non-small cell lung cancer.

Khorrami, M., Jain, P., Khunger, M., Ahmad, U., Stephans, K., Murthy, S., ... Madabhushi, A. (2018). Combination of CT derived radiomic features and lymphovascular invasion status to predict disease recurrence following trimodality therapy in non-small cell lung cancer.. Journal of Clinical Oncology, 36 (15_suppl), e24314-e24314.

Sunday, May 20, 2018

Computer extracted features of cancer nuclei from H&E stained tissues of tumor predicts response to nivolumab in non-small cell lung cancer.

WAng, X., Barrera, C., Velu, P., Bera, K., Prasanna, P., Khunger, M., ... Madabhushi, A. (2018). Computer extracted features of cancer nuclei from H&E stained tissues of tumor predicts response to nivolumab in non-small cell lung cancer.. Journal of Clinical Oncology, 36 (15_suppl), 12061-12061.

Sunday, May 20, 2018

Computer-extracted features relating to spatial arrangement of tumor infiltrating lymphocytes to predict response to nivolumab in non-small cell lung cancer (NSCLC).

Barrera, C., Velu, P., Bera, K., WAng, X., Prasanna, P., Khunger, M., ... Madabhushi, A. (2018). Computer-extracted features relating to spatial arrangement of tumor infiltrating lymphocytes to predict response to nivolumab in non-small cell lung cancer (NSCLC).. Journal of Clinical Oncology, 36 (15_suppl), 12115-12115.

Sunday, May 20, 2018

Computer-extracted stromal features of African-Americans versus Caucasians from H&E slides and impact on prognosis of biochemical recurrence.

Bhargava, H., Leo, P., Elliott, R., Janowczyk, A., Whitney, J., Gupta, S., ... Madabhushi, A. (2018). Computer-extracted stromal features of African-Americans versus Caucasians from H&E slides and impact on prognosis of biochemical recurrence.. Journal of Clinical Oncology, 36 (15_suppl), 12075-12075.

Sunday, May 20, 2018

Correlation of radiomic features with PD-L1 expression in early stage non-small cell lung cancer (ES-NSCLC) to predict recurrence and overall survival (OS).

Patil, P., Bera, K., Vaidya, P., Prasanna, P., Khunger, M., Khunger, A., ... Madabhushi, A. (2018). Correlation of radiomic features with PD-L1 expression in early stage non-small cell lung cancer (ES-NSCLC) to predict recurrence and overall survival (OS).. Journal of Clinical Oncology, 36 (15_suppl), e24247-e24247.

Sunday, May 20, 2018

Image-based risk score to predict recurrence of ER+ breast cancer in ECOG-ACRIN Cancer Research Group E2197.

Verma, N., Harding, D., Mohammadi, A., Goldstein, L., Gilmore, H., Feldman, M., ... Monaco, J. (2018). Image-based risk score to predict recurrence of ER+ breast cancer in ECOG-ACRIN Cancer Research Group E2197.. Journal of Clinical Oncology, 36 (15_suppl), 540-540.

Sunday, May 20, 2018

Predicting neo-adjuvant chemotherapy response from pre-treatment breast MRI using machine learning and HER2 status.

Braman, N., Ravichandran, K., Janowczyk, A., Abraham, J., & Madabhushi, A. (2018). Predicting neo-adjuvant chemotherapy response from pre-treatment breast MRI using machine learning and HER2 status.. Journal of Clinical Oncology, 36 (15_suppl), 582-582.

Monday, May 7, 2018

Radiomic features from pretreatment biparametric MRI predict prostate cancer biochemical recurrence: Preliminary findings: Prostate Cancer Recurrence Prediction

Shiradkar, R., Ghose, S., Jambor, I., Taimen, P., Ettala, O., Purysko, A., ... Madabhushi, A. (2018). Radiomic features from pretreatment biparametric MRI predict prostate cancer biochemical recurrence: Preliminary findings: Prostate Cancer Recurrence Prediction. Journal of Magnetic Resonance Imaging, ().

Friday, May 4, 2018

A resolution adaptive deep hierarchical (RADHicaL) learning scheme applied to nuclear segmentation of digital pathology images

Janowczyk, A., Doyle, S., Gilmore, H., & Madabhushi, A. (2018). A resolution adaptive deep hierarchical (RADHicaL) learning scheme applied to nuclear segmentation of digital pathology images. Computer Methods in Biomechanics and Biomedical Engineering: Imaging and Visualization, 6 (3), 270-276.

Tuesday, May 1, 2018

857 - Machine Learning Analysis of the Whole Rectal Wall on Post-Neoadjuvant Chemoradiation MRI may offer Accurate Identifiction of Rectal Cancer Patients Needing more Aggressive Follow-Up or Surgery

Antunes, J., Selvam, A., Bera, K., Brady, J., Willis, J., Paspulati, R., ... Viswanath, S. E. (2018). 857 - Machine Learning Analysis of the Whole Rectal Wall on Post-Neoadjuvant Chemoradiation MRI may offer Accurate Identifiction of Rectal Cancer Patients Needing more Aggressive Follow-Up or Surgery. Gastroenterology, 154 (6).

Tuesday, May 1, 2018

A Real-Time Wearable FPGA-based Seizure Detection Processor Using MCMC

Marni, L., Hosseini, M., Hopp, J., Mohseni, P., & Mohsenin, T. (2018). A Real-Time Wearable FPGA-based Seizure Detection Processor Using MCMC. IEEE International Symposium on Circuits and Systems (ISCAS), (), 4-Jan.

Case School of Engineering

Electrical, Computer, and Systems Engineering

Electrical, Computer, and Systems Engineering Publications

Make Evasion Harder: An Intelligent Android Malware Detection System

Nuclear shape and orientation features from H&E images predict survival in early-stage estrogen receptor-positive breast cancers

Advances in the computational and molecular understanding of the prostate cancer cell nucleus: CARLETON et al.

Periodicity: A Characteristic of Heart Rate Variability Modified by the Type of Mechanical Ventilation After Acute Lung Injury

Wind farm cooperative control for optimal power generation

Global Stabilization of a Class of Time-Delay Nonlinear Systems with Unknown Control Directions by Nonsmooth Feedback

Cross-Domain Sentiment Classification via A Bifurcation-LSTM

A compressive sensing framework for high-site-density brain dopamine recording with fast-scan cyclic voltammetry

Capacitive wireless power transfer (C–WPT) to neural implants

An FPGA-based Flexible and MIMO-capable GPR System

Adaptive Regulation of Hypersonic Vehicle Systems with Partial Nonlinear Parametrization

Quantitative nuclear histomorphometry predicts oncotype DX risk categories for early stage ER+ breast cancer

High-throughput adaptive sampling for whole-slide histopathology image analysis (HASHI) via convolutional neural networks: Application to invasive breast cancer detection

Novel Quantitative Imaging for Predicting Response to Therapy: Techniques and Clinical Applications

Combination of CT derived radiomic features and lymphovascular invasion status to predict disease recurrence following trimodality therapy in non-small cell lung cancer.

Computer extracted features of cancer nuclei from H&E stained tissues of tumor predicts response to nivolumab in non-small cell lung cancer.

Computer-extracted features relating to spatial arrangement of tumor infiltrating lymphocytes to predict response to nivolumab in non-small cell lung cancer (NSCLC).

Computer-extracted stromal features of African-Americans versus Caucasians from H&E slides and impact on prognosis of biochemical recurrence.

Correlation of radiomic features with PD-L1 expression in early stage non-small cell lung cancer (ES-NSCLC) to predict recurrence and overall survival (OS).

Image-based risk score to predict recurrence of ER+ breast cancer in ECOG-ACRIN Cancer Research Group E2197.

Predicting neo-adjuvant chemotherapy response from pre-treatment breast MRI using machine learning and HER2 status.

Radiomic features from pretreatment biparametric MRI predict prostate cancer biochemical recurrence: Preliminary findings: Prostate Cancer Recurrence Prediction

A resolution adaptive deep hierarchical (RADHicaL) learning scheme applied to nuclear segmentation of digital pathology images

857 - Machine Learning Analysis of the Whole Rectal Wall on Post-Neoadjuvant Chemoradiation MRI may offer Accurate Identifiction of Rectal Cancer Patients Needing more Aggressive Follow-Up or Surgery

A Real-Time Wearable FPGA-based Seizure Detection Processor Using MCMC

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