Team members
- Wesley Xu ([email protected])
- Aditya Mukhija ([email protected])
- Arif Imtiaz Khan ([email protected])
- Pratik Rai ([email protected])
- Deependra Datta ([email protected])
- Shaye Garg ([email protected])
Introduction
Our group explores the benefits of visualizing Fast Healthcare Interoperability Resources (FHIR) data, highlighting how such visualization facilitates better understanding and management of healthcare information. By employing graphical representations, complex patient data become more accessible and interpretable to healthcare providers, enabling quicker and more informed decision-making. Visualization tools can reveal trends, patterns, and anomalies within the data, aiding in diagnosis, treatment planning, and patient care optimization. Additionally, visualizing FHIR data supports interoperability and enhances communication among healthcare teams, contributing to improved patient outcomes.
Code Base Overview
- Boxplot_src.py contains the python source code of the boxplot.
- Boxplot_code_Intro.ipynb contains the Introduction, parameters, AI comments and example result graph for Disease: 'Asthma'.
- BarChart.py contains the python source code of the bar chart with the intial result for Disease: 'Asthma'
- LineGraph.py contains the python source code of the line graph with the intial result for Disease: 'Asthma'
- Mind Map for our Senario
back-end:
- Boxplot (User Input: NAME of the disease) (Done by Wesley)
- Bar Chart (Done by Deependra)
- Line GRAPH (Done by Deependra)
front-end(the code is in another branch):
- User Interface
- Adjust FastAPI framework with front-end and back-end.