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cs.AI2026
When Clean Signals Are Not Enough: Detecting Structural Ambiguity for Safe Wearable Stress Classification
Saba A. Farahani, Hung Cao, Amir M. Rahmani
Wearable stress classifiers can achieve strong average performance while failing completely for a particular individual. On WESAD, a Random Forest reaches 93.0% mean accuracy yet y…
cs.AI2026
T2D-Bench: Evidence-Gated Evaluation of LLM Outputs for Type 2 Diabetes Using a Multi-Layer Clinical-Lifestyle Knowledge Graph
Saba A. Farahani, Hung Cao, Ramesh Jain +1
Large language models (LLMs) can produce clinically fluent recommendations for type 2 diabetes while failing to satisfy guideline constraints or explicitly justify lifestyle-relate…
cs.AI2024
Food Recommendation as Language Processing (F-RLP): A Personalized and Contextual Paradigm
Ali Rostami, Ramesh Jain, Amir M. Rahmani
State-of-the-art rule-based and classification-based food recommendation systems face significant challenges in becoming practical and useful. This difficulty arises primarily beca…