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20242026
most citedAI Agents for Conversational Patient Triage: Preliminary Simulation-Based Evaluation with Real-World EHR Data

2 citations · 4 across the 5 of their papers we have counts for

collaborators

7 papers

cs.CV2026

iSight: Towards expert-AI co-assessment for improved immunohistochemistry staining interpretation

Jacob S. Leiby, Jialu Yao, Pan Lu +17

Immunohistochemistry (IHC) provides information on protein expression in tissue sections and is commonly used to support pathology diagnosis and disease triage. While AI models for…

cs.AI2026

STEER: Inference-Time Risk Control via Constrained Quality-Diversity Search

Eric Yang, Jong Ha Lee, Jonathan Amar +2

Large Language Models (LLMs) trained for average correctness often exhibit mode collapse, producing narrow decision behaviors on tasks where multiple responses may be reasonable. T…

cs.CL20252 cited

An AI-Based Behavioral Health Safety Filter and Dataset for Identifying Mental Health Crises in Text-Based Conversations

Benjamin W. Nelson, Celeste Wong, Matthew T. Silvestrini +6

Large language models often mishandle psychiatric emergencies, offering harmful or inappropriate advice and enabling destructive behaviors. This study evaluated the Verily behavior…

cs.CL2025

FHIR-AgentBench: Benchmarking LLM Agents for Realistic Interoperable EHR Question Answering

Gyubok Lee, Elea Bach, Eric Yang +5

The recent shift toward the Health Level Seven Fast Healthcare Interoperability Resources (HL7 FHIR) standard opens a new frontier for clinical AI, demanding LLM agents to navigate…

cs.CL20252 cited

AI Agents for Conversational Patient Triage: Preliminary Simulation-Based Evaluation with Real-World EHR Data

Sina Rashidian, Nan Li, Jonathan Amar +7

Background: We present a Patient Simulator that leverages real world patient encounters which cover a broad range of conditions and symptoms to provide synthetic test subjects for…

cs.LG2025

Sleepless Nights, Sugary Days: Creating Synthetic Users with Health Conditions for Realistic Coaching Agent Interactions

Taedong Yun, Eric Yang, Mustafa Safdari +13

We present an end-to-end framework for generating synthetic users for evaluating interactive agents designed to encourage positive behavior changes, such as in health and lifestyle…