A deep learning classifier for prediction of pathological complete response to neoadjuvant chemotherapy from baseline breast DCE-MRI. - Kavya Ravichandran; Nathaniel Braman; Andrew Janowczyk; Anant Madabhushi (Computer-Aided Diagnosis, 2018)

Vascular Network Organization via Hough Transform (VaNgOGH): A Novel Radiomic Biomarker for Diagnosis and Treatment Response. - Nathaniel Braman; Prateek Prasanna; Mehdi Alilou; Niha G. Beig; Anant Madabhushi (MICCAI (2), 2018)

Disease Detection in Weakly Annotated Volumetric Medical Images using a Convolutional LSTM Network. - Nathaniel Braman; David Beymer; Ehsan Dehghan (CoRR, 2018)

Morphology of vascular network in eyes with diabetic macular edema varies based on tolerance of aflibercept treatment interval length: preliminary findings. - Prateek Prasanna; Justis Ehlers; Nathaniel Braman; Natalia Figueredo; Vishal Bobba; Sumit Sharma 005; Sunil Srivastava; Anant Madabhushi (Biomedical Applications in Molecular, Structural, and Functional Imaging, 2019)

Response Estimation Through Spatially Oriented Neural Network and Texture Ensemble (RESONATE). - Jeffrey E. Eben; Nathaniel Braman; Anant Madabhushi (MICCAI (4), 2019)

A combination of intra- and peri-tumoral deep features from prostate bi-parametric MRI can distinguish clinically significant and insignificant prostate cancer. - Amogh Hiremath; Rakesh Shiradkar; Nathaniel Braman; Prateek Prasanna; Ardeshir R. Rastinehad; Andrei S. Purysko; Anant Madabhushi (Computer-Aided Diagnosis, 2020)

Computationally derived cytological image markers for predicting risk of relapse in acute myeloid leukemia patients following bone marrow transplantation. - Sara ArabYarmohammadi; Zelin Zhang; Patrick Leo; Marjan Firouznia; Andrew Janowczyk; Haojia Li; Nathaniel M. Braman; Kaustav Bera; Behtash G. Nezami; Howard Meyerson; Jun Xu 005; Leland Metheny; et al. (Digital Pathology, 2020)

Computer extracted features related to the spatial arrangement of tumor-infiltrating lymphocytes predict overall survival in epithelial ovarian cancer receiving adjuvant chemotherapy. - Sepideh Azarianpour; Germán Corredor; Kaustav Bera; Patrick Leo; Nathaniel Braman; Pingfu Fu; Haider Mahdi; Anant Madabhushi (Digital Pathology, 2020)

Deep learning-based prediction of response to HER2-targeted neoadjuvant chemotherapy from pre-treatment dynamic breast MRI: A multi-institutional validation study. - Nathaniel Braman; Mohammed El Adoui; Manasa Vulchi; Paulette Turk; Maryam Etesami; Pingfu Fu; Kaustav Bera; Stylianos Drisis; Vinay Varadan; Donna Plecha; Mohammed Benjelloun; Jame Abraham; et al. (CoRR, 2020)

Deep Orthogonal Fusion: Multimodal Prognostic Biomarker Discovery Integrating Radiology, Pathology, Genomic, and Clinical Data. - Nathaniel Braman; Jacob W. H. Gordon; Emery T. Goossens; Caleb Willis; Martin C. Stumpe; Jagadish Venkataraman (MICCAI (5), 2021)

Application of Federated Learning in Medical Imaging. - Ehsan Degan; Shafiq Abedin; David Beymer; Angshuman Deb; Nathaniel Braman; Benedikt Graf; Vandana V. Mukherjee (Federated Learning, 2022)

Novel Radiomic Measurements of Tumor- Associated Vasculature Morphology on Clinical Imaging as a Biomarker of Treatment Response in Multiple Cancers. - Nathaniel Braman; Prateek Prasanna; Kaustav Bera; Mehdi Alilou; Mohammadhadi Khorrami; Patrick Leo; Maryam Etesami; Manasa Vulchi; Paulette Turk; Amit Gupta; Prantesh Jain; Pingfu Fu; et al. (CoRR, 2022)