Using deep neural networks to interpret quantitative image analysis and gene expression data in lung cancer (from Smedley et al)

Overview

In the current data-rich healthcare environment, our capacity to collect vast amounts of longitudinal observational data needs to be matched with a comparable ability to continuously learn from the data and tailor clinical decisions to an individual. The Hsu Lab develops and validates computational tools to extract clinically meaningful insights from multimodal datasets. We apply artificial intelligence (AI)/machine learning (ML) techniques to mine and analyze clinical, diagnostic imaging, and molecular data, harnessing the combination of genomic and environmental information to achieve evidence-based management of patients and precision health.


Lab activities revolve around three areas:

Focus Areas

Active Funding