Trace: • project-01

Data Visualization and Representation of a Quantitative Patient State in Radiation Oncology

Last updated: 10/26/17, 8:57 P.M.

Summary

This project will improve upon some features of OncoBrowser, specifically longitudinal patient outcome charts and star charts to visualize the patient condition. The ultimate goal of this project is to make these features easier for clinicians to use and view/add data.

Student: Liza Mathews
Mentor(s): Dr. Todd McNutt, Dr. Russell Taylor, Michael Bowers

Background, Specific Aims, and Significance

OncoBrowser is a tool for clinicians to view patient data, history, and treatment plans, and improving on features within OncoBrowser will allow clinicians to access and view patient data in a more organized fashion. The specific goals of this project are…

To make longitudinal patient outcome charts that allow clinicians to easily see patient data over various visits
To improve clarity of star charts that represent patient data
To make data entry easier (interactive graphs)

Deliverables

Minimum: (Expected by 11/14/17)
1. Star chart module improvements

Expected: (Expected by 12/05/17)
1. Star chart module improvements
2. Proper documentation of code

Maximum: (Expected by 12/15/17)
1. Making patient outcome charts and star chart module more interactive (i.e. click on graph to plot point)

Technical Approach

All front end components will be written in C#, and SQL will be used to access the Mosaiq database. Additionally, some charting tools such as Chart.js (simple and flexible JavaScript charting for designers & developers) may be used to make graphs more interactive. Embedding Javascript within the current code can add some new functionality to the modules. For example, plotly.js (Javascript graphing library) offers some interactive graphs that allow one to add and delete points on a plot. Another potential Javascript library for manipulating data based on documents is D3.js, which is extremely fast and able to support large data sets and dynamic behaviors for interaction and animation. These three libraries (Chart.js, plotly.js, and D3.js) all offer additionally functionality that can be useful to improving OncoBrowser features.