Hi! This is my first parkinson’s project devlog.

I started this project around 3 months ago, and I knew nothing about machine learning then. In that time, I learnt everything I needed for my project. So far, I have made a decent pipeline to identify biomarkers.

I’m using an NCBI GEO Superseries for training, and I was planning on using a Portuguese cohort for extra real-world data tests.

Today, when I was comparing whether to use XGBoost or Random Forest, it gave accuracies of 93-95%, but after more tests, I realized that my AUC rn is around 70%.

Tomorrow, I’m going to try switching from XGBoost + Boruta feature selection to Logistic Regression to see if my AUC can be brought up to at least 80.