MedCUA-Bench: A Screenshot-Only Benchmark for Clinical Computer-Use Agents
On the map: LLM agents and tool use → Medical and scientific domain agents
Abstract (arXiv)
Computer-use agents could automate repetitive screen-based clinical work, but their reliability in medical graphical user interfaces remains largely unvalidated. Existing benchmarks focus on general web or desktop tasks and underrepresent medical software, which requires domain knowledge, exhibits markedly different UI design from mainstream applications, lacks public testing environments, and demands safety validation beyond task completion. We introduce MedCUA-Bench, an interactive benchmark for clinical computer-use agents. It covers 18 clinical scenarios across 10 medical domains, reconstructed from real product manuals and open-source medical systems to capture authentic clinical interfaces while avoiding licensing and privacy constraints. Each task ships with paired intent- and step-level goals to disentangle clinical reasoning from UI execution, and is evaluated by a deterministic checker over task completion and five clinical safety dimensions. Across 23 agents, the best closed-source model reaches 54.2% strict success, while all models remain below 9% on the real OpenEMR. Open-source agents average only 2.5%, with the best reaching 16.2%. MedCUA-Bench exposes the gap between current agents and reliable clinical software use, providing a reproducible testbed for future research.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). Placed in Medical and scientific domain agents, one of 16 directions in LLM agents and tool use. Builds on 16 of its 29 references that are in the map. First posted on arXiv 2 Jun 2026.
Builds on
16 of 29 references.
Closest ancestors · 3
Same direction, newest first
- 2026HealthAdminBench: Evaluating Computer-Use Agents on Healthcare Administration Tasks10 Apr
- 2025MedAgentBench: A Realistic Virtual EHR Environment to Benchmark Medical LLM Agents24 Jan
- 2024AgentClinic: a multimodal agent benchmark to evaluate AI in simulated clinical environments13 May
Other references · 13
- 2023Efficient Memory Management for Large Language Model Serving with PagedAttentioncited by 5,944
- 2023WebArena: A Realistic Web Environment for Building Autonomous Agentscited by 2,006
- 2022WebShop: Towards Scalable Real-World Web Interaction with Grounded Language Agentscited by 1,251
- 2024OSWorld: Benchmarking Multimodal Agents for Open-Ended Tasks in Real Computer Environmentscited by 1,195
- 2024GPT-4V(ision) is a Generalist Web Agent, if Groundedcited by 563
- 2024WorkArena: How Capable Are Web Agents at Solving Common Knowledge Work Tasks?cited by 363
- 2018Reinforcement Learning on Web Interfaces Using Workflow-Guided Explorationcited by 284
- 2024Windows Agent Arena: Evaluating Multi-Modal OS Agents at Scalecited by 223
- 2024The BrowserGym Ecosystem for Web Agent Researchcited by 161
- 2024SpreadsheetBench: Towards Challenging Real World Spreadsheet Manipulationcited by 111
- 2024ScreenAgent: A Vision Language Model-driven Computer Control Agentcited by 102
- 2024MedCalc-Bench: Evaluating Large Language Models for Medical Calculationscited by 70
1 more
Built on by
Citing papers per year: 2026: 4.
4 papers.
- 2026How Benchmarks Mis-Score Computer-Use Agentscited by 4
- 2026Synthetic Hospital: An Open, Verifiable, Physician-Validated Longitudinal EHR Benchmarkcited by 0
- 2026KlinikeBench: Evaluating Language Models Beyond Diagnostic Accuracycited by 0
- 2026MedImageOSWorld: Benchmarking GUI Agents for Medical Image Consolescited by 0
- 2026MedImageOSWorld: Benchmarking GUI Agents for Medical Image Consoles3 Oct 2026
- 2026KlinikeBench: Evaluating Language Models Beyond Diagnostic Accuracy29 Sep 2026
- 2026Synthetic Hospital: An Open, Verifiable, Physician-Validated Longitudinal EHR Benchmark24 Sep 2026
- 2026How Benchmarks Mis-Score Computer-Use Agents30 Jul 2026
Similar, not cited
Close in wording, no citation either way
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