FKSUDDAPre Predicts Drug–Disease Associations With High Accuracy

Zuo et al. publish FKSUDDAPre on February 5, 2026, a framework that predicts drug–disease associations using Mol2vec and K-BERT for drugs and MeSH with DeepWalk for diseases. The system uses AMDKSU resampling, F-test feature selection, and an XGBoost/Decision Tree/Random Forest/HyperFast ensemble, achieves average AUC 0.9725 (≈3.88% improvement), and validates many top candidates for Alzheimer’s and Parkinson’s disease.