Description

Abstract: Prediction of microscopic tumor spread to regional lymph nodes can assist in radiation planning for cancer treatment. However, it is still challenging to predict tumor spread. In this paper, we present a unique approach to modeling how tumor cells disseminate to form regional metastases. This involves leveraging well established knowledge resources and commonly held notions of how cancer spreads. Using patient data, we utilized our approach to create a model of metastasis for the subset of head and neck squamous cell carcinoma that arises in the mucosa of the lateral tongue. The model was created using a training set extracted from the clinical records of 50 patients with tumors of this type who presented to the University of Washington head and tumor board over a three and half year period. The test sets consist of four case series drawn from the literature.

Learning Objective 1: After participating in this session, the learner should be better able to:
Use a structured knowledge representation to build markov models of biomedical processes

Authors:

Hyunggu Jung (Presenter)
University of Washington

Anthony Law, University of Washington
Eli Grunblatt, University of Washington
Lucy Wang, University of Washington
Aaron Kusano, University of Washington
Jose Mejino, University of Washington
Mark Whipple, University of Washington

Themes