Clinical Trial Outcome Prediction

Part 2: Predicting clinical trial outcomes using XGBoost

In the first part of this series I focused on embedding multi-modal real-world data derived from ClinicalTrials.gov. In this article I will implement a basic XGBoost model, train it on the embeddings we created in Part 1 and compare its performance to that of the HINT model (a hierarchical graph neural net) by which this project was inspired.

These are the steps I will follow in …

article basic clinical clinical trial clinical trials data embedding embeddings gov health-data-science hierarchical large language models multi-modal part performance prediction predictive modeling series series i towards-data-science train world xgboost