Overview

In this assignment, you will explore deep learning applied to electronic health records using the MIMIC-III dataset. In the first part of the assignment, you will predict daily sepsis, myocardial infarction (MI), and vancomycin antibiotic administration over two week patient ICU courses recorded in patients' electronic health records. In the second and third parts of the assignment, you will work with clincial text embeddings to predict ICU patient readmissions.

Assignment Setup Instructions

1. Navigate to your VM instance on GCP and ensure it is shut off. Click into it and click EDIT.
   • Change machine type to n1-highmem-8 (8 vCPU, 52 GB memory).
   • Change GPU type to NVIDIA Tesla T4.
   • Scroll to the bottom of the page and click SAVE.
2. Like with the previous assignment, download the assignment files on your VM instance and then unzip them:

   
                       wget https://biods220.stanford.edu/downloads/assign2.zip
                       unzip assign2.zip
                     

You are all set! Good luck and we hope you learn a lot on Assignment 2!

What to hand in for this assignment: Submit one PDF file containing all your notebook solutions (code + written). To convert your notebook to PDF, go to File > Download as > PDF via LaTeX. Alternatively, if you encounter issues with converting to PDF using LaTeX, you can also convert to HTML (File > Download as > HTML) and then "Save to PDF" by printing. Concatenate the PDFs from both parts into one and make sure that both the coding sections and the written sections are visible in the PDFs prior to submission.