======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)
    - Star chart module improvements

  * **Expected:** (Expected by 12/05/17)
    - Star chart module improvements
    - Proper documentation of code

  * **Maximum:** (Expected by 12/15/17)
    - 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. 
======Dependencies======
{{:courses:507:project-01:screen_shot_2017-10-26_at_8.53.41_pm.png?600|}}
======Milestones and Status ======
{{:courses:507:project-01:screen_shot_2017-10-26_at_8.52.33_pm.png?600|}}

======Reports and presentations======

  * Project Plan
    * {{:courses:507:Project-01:proposalproject_planpresentation.pdf| Project plan presentation}}
    * {{[:courses:507:Project-01:project_proposal.pdf]|Project plan proposal}}
  * Project Background Reading 
    * See Bibliography below for links.
  * Project Checkpoint
    * {{:courses:507:Project-01:checkpoint_presentation.pdf| Project checkpoint presentation}}
  * Paper Seminar Presentations
    * here provide links to all seminar presentations
  * Project Final Presentation
    * {{:courses:507:Project-01:final_poster_pdf.pdf|PDF of Poster}}
  * Project Final Report
    * {{:courses:507:Project-01:final_report.pdf|Final Report}}
    * links to any appendices or other material

======Project Bibliography=======

======Other Resources and Project Files======
  * Plotly.js library:  https://plot.ly/javascript/getting-started/
  * Chart.js tools:  http://www.chartjs.org/
  * D3.js library:  https://d3js.org/