AI for Cancer

Pearson Lab has been at the forefront of research leveraging AI, especially deep learning, to transform cancer care and outcomes. Our work has focused on developing robust deep learning models to analyze complex cancer data, including digital pathology slides, radiology images, and multimodal data, to guide clinical decision-making. Key innovations have included novel techniques to improve model performance, such as synthetic cancer histology generation, uncertainty quantification, and the application of deep learning to pathology for predicting cancer recurrence.

Clinical Machine Learning

Pearson Lab has worked on developing and validating clinical machine learning models to guide decision-making and improve outcomes across cancer types. A core focus has been building prognostic models using features from clinical data, genomics, digital pathology, radiology data, and combinations of these data types. The work provides a framework for developing machine learning models that clinicians can trust and reliably act upon to benefit patient care. Overall, Pearson Lab is at the leading edge of demonstrating how many different data types can be thoughtfully and transparently translated to improve clinical decision-making and outcomes for cancer patients.

Cancer Systems Biology

Pearson Lab has developed integrated laboratory and computational platforms to better understand the complexities of human cancers. We developed a live-cell imaging platform to observe and collect information about interactions between tumor cells, immune cells, and treatments. This information is passed into a custom-built multi-scale agent-based mathematical model of the tumor, which can be used for detailed simulations to optimize treatment combinations.

Head & Neck Cancer Clinical Research

Pearson Lab conducts interventional clinical and translational research. Our lab leads multiple clinical trials to evaluate new treatment strategies, and organizes and analyzes samples derived from these studies. Pearson Lab interfaces closely with the University of Chicago Head and Neck Cancer Program, which is an internationally-recognized leader in treatment innovation.

Quantum Computing for Oncology