Patient No-show Prediction Uncertainty Modeling Compressed Data and Code
Published: 21 July 2025| Version 1 | DOI: 10.17632/mcwpryrs4k.1
Contributors:
Arin Brahma, Description
The compressed content include data and software programs needed to reproduce the results related to development of patient no-show prediction models, SHAP analysis for interpretability, and uncertainty modeling to evaluate the ML models.
Files
Steps to reproduce
Kindly follow the step-by-step instructions provided in the Readme file included in the ZIP file content. Kindly keep all programs and data in the same folder.
Institutions
- Loyola Marymount University
Categories
Machine Learning, Healthcare Research, Interpretable Machine Learning