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.
Barrera, C., Velu, P., Bera, K., WAng, X., Prasanna, P., Khunger, M., Khunger, A., Velcheti, V., Romero, E., & 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.
Verma, N., Harding, D., Mohammadi, A., Goldstein, L., Gilmore, H., Feldman, M., Tomaszewski, J., Basavanhally, A., Lloyd, M., Fu, P., Ganesan, S., Davidson, N., Madabhushi, A., & 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.
Khorrami, M., Jain, P., Khunger, M., Ahmad, U., Stephans, K., Murthy, S., Velcheti, V., & 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.
Bhargava, H., Leo, P., Elliott, R., Janowczyk, A., Whitney, J., Gupta, S., Yamoah, K., Rebbeck, T., Feldman, M., Lal, P., & 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.
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.
WAng, X., Barrera, C., Velu, P., Bera, K., Prasanna, P., Khunger, M., Khunger, A., Velcheti, V., & 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.
Patil, P., Bera, K., Vaidya, P., Prasanna, P., Khunger, M., Khunger, A., Velcheti, V., & 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.
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.
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.
Antunes, J., Selvam, A., Bera, K., Brady, J., Willis, J., Paspulati, R., Madabhushi, A., Delaney, C., & 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).
Orooji, M., Alilou, M., Rakshit, S., Beig, N., Khorrami, M., Rajiah, P., Thawani, R., Ginsberg, J., Donatelli, C., Yang, M., Jacono, F., Gilkeson, R., Velcheti, V., Linden, P., & Madabhushi, A.(2018).Combination of computer extracted shape and texture features enables discrimination of granulomas from adenocarcinoma on chest computed tomography.Journal of Medical Imaging,5(2).
Nirschl, J., Janowczyk, A., Peyster, E., Frank, R., Margulies, K., Feldman, M., & Madabhushi, A.(2018).A deep-learning classifier identifies patients with clinical heart failure using whole-slide images of H&E tissue.PLoS ONE,13(4).
Leo, P., Gawlik, A., Zhu, G., Feldman, M., Gupta, S., Veltri, R., & Madabhushi, A.(2018).MP35-02 COMPUTER-EXTRACTED FEATURES OF NUCLEAR AND GLANDULAR MORPHOLOGY FROM DIGITAL H&E TISSUE IMAGES PREDICT PROSTATE CANCER BIOCHEMICAL RECURRENCE AND METASTASIS FOLLOWING RADICAL PROSTATECTOMY.The Journal of Urology,199(4),e446-e447.
Nirschl, J., Janowczyk, A., Peyster, E., Frank, R., Margulies, K., Feldman, M., & Madabhushi, A.(2018).A deep-learning classifier identifies patients with clinical heart failure using whole-slide images of H and e tissue.PLoS ONE,13(4).
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.
Leo, P., Shankar, E., Elliott, R., Janowczyk, A., Janaki, N., MacLennan, G., Madabhushi, A., & Gupta, S.(2018).MP35-09 COMBINATION OF NF-?B/P65 NUCLEAR LOCALIZATION AND GLAND MORPHOLOGIC FEATURES IS PREDICTIVE OF BIOCHEMICAL RECURRENCE.The Journal of Urology,199(4).
Li, H., Leo, P., Nezami, B., Akgul, M., Elliott, R., Harper, H., Janowczyk, A., MacLennan, G., & Madabhushi, A.(2018).MP08-16 COMBINATION OF NUCLEAR ORIENTATION AND SHAPE FEATURES IN H&E STAINED IMAGES DISTINGUISH CONSENSUS LOW AND HIGH GRADE BLADDER CANCER.The Journal of Urology,199(4).
Janowczyk, A., Shankar, E., Leo, P., Madabhushi, A., Elliott, R., & Gupta, S.(2018).Combination of nuclear NF-kB/p65 localization and gland morphological features from surgical specimens appears to be predictive of early biochemical recurrence in prostate cancer patients.Medical Imaging: Digital Pathology.
WAng, X., Velcheti, V., Vaidya, P., Bera, K., Madabhushi, A., Khunger, A., Patil, P., & Choi, H.(2018).RaPtomics: integrating radiomic and pathomic features for predicting recurrence in early stage lung cancer.Medical Imaging: Digital Pathology.
Romero Castro, E., Corredor, G., Lu, C., Madabhushi, A., WAng, X., & Velcheti, V.(2018).A watershed and feature-based approach for automated detection of lymphocytes on lung cancer images.Medical Imaging: Digital Pathology.
Peyster, E., Madabhushi, A., & Margulies, K.(2018).Advanced Morphologic Analysis for Diagnosing Allograft Rejection: The Case of Cardiac Transplant Rejection.Transplantation.
Ravichandran, K., Braman, N., Janowczyk, A., & Madabhushi, A.(2018).A deep learning classifier for prediction of pathological complete response to neoadjuvant chemotherapy from baseline breast DCE-MRI.Medical Imaging: Computer-Aided Diagnosis.
Chirra, P., Bloch, N., Rastinehead, A., Purysko, A., Madabhushi, A., Viswanath, S., Leo, P., Yim, M., & Rosen, M.(2018).Empirical evaluation of cross-site reproducibility in radiomic features for characterizing prostate MRI.Medical Imaging: Computer-Aided Diagnosis.
