Breast Cancer Prediction
This notebook illustrates how one can use random forest models for prediction. For this illustration, we have taken an example for breast cancer prediction using UCI'S breast cancer diagnostic data set. The purpose here is to use this data set to build a predictive model of whether a breast mass image indicates benign or malignant tumor.
Connecting to OCHIN DB
This notebook is for AIM AHEAD users who have access to the OCHIN dataset. To learn more about the OCHIN data, see the Accessing OCHIN Data and Understanding OCHIN Data sections of the user guide.
This notebook will walk you through how to connect to the OCHIN DB while in a Jupyter Notebook. Before you begin, make sure that you have access to the data and check to make sure the db-credentials.txt file is located in your home directory.
Investigating EHR data from PIC-SURE
The purpose of this notebook is to help researchers get started with EHR analysis using clinical data exported from PIC-SURE.