This repository contains an analysis of a single patient, and an analysis of over 70 patients with diabetes. For the latter group, a model is included that can be used to predict a sample blood sugar at any given time of the day.
analysis.ipynb- contains an analysis of patient 0model.ipynb- contains an analysis of all 70 patients, as well as a random forest prediction model
In June of 2022, I was diagnosed with Type II diabetes, and in September of that year Type I diabetes. I would love to replace patient 0 with my own readings if I ever aquire a continous BG monitor.
Kahn,Michael. Diabetes. UCI Machine Learning Repository. https://doi.org/10.24432/C5T59G.