3 papers
cs.CL2026
A knowledge-guided agentic framework for mitigating patient-context ambiguity in health queries
Mahyar Abbasian, Saba A. Farahani, Arshia Ilaty +3
Patients often submit short, underspecified queries to healthcare chatbots that lack the patient-specific information needed to determine an appropriate response. Although these qu…
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…