Panchamahabhuta Genomics: Tridosha Disease Prediction Model
Abstract
Trained Random Forest model for predicting disease category from protein Tridosha composition. Achieves 91.2% accuracy across 13 disease categories using 68,573 ClinVar pathogenic variants. Includes protein Prakriti database and feature encoders. Part of the Panchamahabhuta Genomics framework described in Pande et al. (2025).
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 20 March 2026
- Document type
- Dataset