Builds a predictive model
of cancer survival
This web application builds a predictive model of cancer survival based on user-selected features.
Select features desired for the model using the checkboxes. Click Submit to generate the model and display predictions. Data for this web application came from The Cancer Genome Atlas for Acute Myeloid Leukemia. Data was extracted from XML files and stored in a Postgres database on this server. This python web application is powered by Flask. The numpy and sklearn packages are used to handle the data and perform linear regression. The psycopg2 package is used to access the database. Graph generated with plotly.
The process of developing this application is described on Matthew Theisen's Data Blog.