Retrieval-aligned Tabular Foundation Models Enable Robust Clinical Risk Prediction in Electronic Health Records Under Real-world Constraints

Retrieval-aligned Tabular Foundation Models Enable Robust Clinical Risk Prediction in Electronic Health Records Under Real-world Constraints explores A retrieval-aligned framework for robust clinical risk prediction from electronic health records that overcomes data complexity and imbalance.. Commercial viability score: 7/10 in Clinical AI.