Lillian McHugh ‘24
Machine learning cancer immunotherapy
Lillian McHugh ‘24, Biology and Mathematics major
Faculty Mentor: Dr. Joseph Shomberg, Mathematics
The aim of our research is to establish the viability of machine learning to the prediction of TGF-β cancer treatment success (or failure). Our method begins by analyzing a dynamical system model of cancer invasion with a subsequent immune system response. Important model parameters are identified. Numerical simulations are then run with suitably randomly chosen parameters to create a simulated dataset that is used to train different predictive machine learning models. When presented with new data, the classifier’s accuracy is recorded. We can celebrate one model’s accuracy at 98.65% and look forward to applying the model on real-world data.
Poster Presentation: Thursday, April 27, 2 – 4 p.m.
