Institute Fellow Publishes on Machine Learning in Medical Field

Vijaya Kolachalama, a faculty member within the Section of Computational Biomedicine in the Boston University School of Medicine, leverages machine learning, image processing, and statistical modeling to understand pathophysiological mechanisms relevant to forecasting the likely course of various diseases. 

Funded through the Hariri Institute Research Incubation Award program in January of 2017, Kolachalama’s project, Machine Learning-Driven Quantification of Pathological Fibrosis for Prognostic Relevance, used the AI method of deep learning and applied it to routine renal biopsy images in order to develop better, more effective treatments. Following on the success of this incubated research, Kolachalama has since been published in the Journal of the American Society of Nephrology, a prestigious journal in the field of Nephrology, and KIReports. Additionally, he was featured on the cover of Science Translational Medicine, a journal published by the American Association for the Advancement of Science.

[Read more on the School of Medicine website]