A tumor board is a discussion among multiple physicians to determine the most appropriate treatment option for a specific cancer patient with a complex disease course. Treatment recommendations are often influenced by previous experience with patients exhibiting similar disease courses. While patient-related image data is displayed during the discussion, clinical patient data, such as the course of tumor days, histological parameters and previously performed treatments, cannot be retrieved at any time and must be repeatedly asked for or memorized. In addition, there is not yet a method to automatically identify and visualize the k most similar patients with their respective therapy trajectories.
Goal: To support physicians during tumor boards in therapy planning for skin cancer patients, the goal of the project is to develop a tumor board visual analytics system that (i) effectively displays longitudinal patient data and (ii) identifies and visualizes characteristics and treatment histories of the most similar previously treated patients.
Team size: 2-3 Master FIN students or Bachelor/Master Thesis
Requirements: Programming experience in D3, Python, or R; critical thinking
References:
[1] Hörbrügger M, Steinhauer N, et al. “Comprehensive Visualization of Longitudinal Patient Data for the Dermatological Oncological Tumor Board.” Proc. of EuroVis 2020. URL: https://diglib.eg.org/handle/10.2312/evs20201067
[2] Prakash S, Unnikrishnan V, Pryss R, Kraft R, Schobel J, Hannemann R, Langguth B, Schlee W, Spiliopoulou M. “Interactive System for Similarity-Based Inspection and Assessment of the Well-Being of mHealth Users.” Entropy. 2021; 23(12):1695. https://doi.org/10.3390/e23121695