Rami Vanguri

Rami Vanguri, PhD

Assistant Professor, Department of Medicine

Keywords
machine learning, radiomics, deep learning, computational pathology, spatial transcriptomics , multiplexed imaging, MRI, CT
Summary

The goal of my research is to leverage complementary disease characterizations of histopathological and radiological data to develop multimodal biomarkers. Tissue-based spatial profiling allows for the localization and quantification of features within the tissue microenvironment, providing insight into disease pathology. In contrast, radiological imaging is a non-invasive method which captures macroscopic characteristics of disease, which can be quantitatively characterized using computational techniques such as deep learning and radiomics. By integrating quantitative characterizations of these data sources, I aim to develop novel biomarkers that can improve disease diagnosis, prognosis, and treatment response prediction. Through collaboration and innovative methodological approaches, I aim to advance precision medicine over neoplastic and non-neoplastic disease.

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PhD from University of Pennsylvania

Barcia Durán, José Gabriel; Das, Dayasagar; Gildea, Michael; Amadori, Letizia; Gourvest, Morgane; Kaur, Ravneet; Eberhardt, Natalia; Smyrnis, Panagiotis; Cilhoroz, Burak; Sajja, Swathy; Rahman, Karishma; Fernandez, Dawn M; Faries, Peter; Narula, Navneet; Vanguri, Rami; Goldberg, Ira J; Fisher, Edward A; Berger, Jeffrey S; Moore, Kathryn J; Giannarelli, Chiara

Nature cardiovascular research. 2024 Dec; 3(12):1482-1502