CST 499 Week 2
Progress Update: Onco-Logic This week, our team completed our individual contributions to the cancer-subtype classification project and officially moved into the final phase of Onco-Logic: building models to extract structured insights from free-text pathology reports. We’ve begun collecting the data, exploring the corpus structure, and running early-stage exploratory data analysis. My best-performing approach on the cancer-subtype task came from selecting the top 350 genes based on variance. Using this reduced feature set, I trained a LinearSVC model that achieved nearly perfect accuracy, precision, and recall across all five cancer types. These results were strong both in terms of raw performance and interpretability, especially when paired with SHAP to visualize feature importance. With the modeling work complete, I also helped prepare materials for dashboard integration and documentation. Looking ahead, our team will be focusing on developing the NLP preprocessing pipeli...