HealthAgentBench is a new benchmark of 54 healthcare agent tasks where even the strongest frontier AI agent reaches only about 42% success rate on end-to-end clinical workflows.
Fries, and Nigam H
4 Pith papers cite this work, alongside 20 external citations. Polarity classification is still indexing.
4
Pith papers citing it
20
external citations · external index
years
2026 4verdicts
UNVERDICTED 4representative citing papers
CHI-Bench shows current AI agents achieve at most 28% success on long-horizon healthcare workflows that require dense policy adherence, multi-role handoffs, and multi-turn interactions.
CLR-voyance reformulates inpatient reasoning as POMDP with clinician-validated outcome rubrics, yielding an 8B model that outperforms larger frontier models on the authors' new benchmark.
Proposes MedRLM, a recursive agent-based multimodal framework for long-context clinical reasoning, sensor-guided screening, and referral optimization using a Clinical Evidence Graph Memory.
citing papers explorer
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HealthAgentBench: A Unified Benchmark Suite of Realistic Agentic Healthcare Environments for Challenging Frontier AI Agents
HealthAgentBench is a new benchmark of 54 healthcare agent tasks where even the strongest frontier AI agent reaches only about 42% success rate on end-to-end clinical workflows.
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CHI-Bench: Can AI Agents Automate End-to-End, Long-Horizon, Policy-Rich Healthcare Workflows?
CHI-Bench shows current AI agents achieve at most 28% success on long-horizon healthcare workflows that require dense policy adherence, multi-role handoffs, and multi-turn interactions.
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CLR-voyance: Reinforcing Open-Ended Reasoning for Inpatient Clinical Decision Support with Outcome-Aware Rubrics
CLR-voyance reformulates inpatient reasoning as POMDP with clinician-validated outcome rubrics, yielding an 8B model that outperforms larger frontier models on the authors' new benchmark.
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MedRLM: Recursive Multimodal Health Intelligence for Long-Context Clinical Reasoning, Sensor-Guided Screening, Evidence-Grounded Decision Support, and Community-to-Tertiary Referral Optimization
Proposes MedRLM, a recursive agent-based multimodal framework for long-context clinical reasoning, sensor-guided screening, and referral optimization using a Clinical Evidence Graph Memory.