arXiv:2606.03203v1 Announce Type: new Abstract: 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 clinic
The development of specific benchmarks for clinical computer-use agents is emerging now due to the increasing maturity of AI agent technology and the recognized need for domain-specific validation beyond general-purpose benchmarks.
This benchmark is crucial for accelerating the reliable and safe deployment of AI agents in highly sensitive medical environments, potentially automating significant portions of clinical administrative and diagnostic work.
The introduction of MedCUA-Bench shifts the focus from theoretical AI agent capabilities to practical, validated application within complex medical graphical user interfaces, specifically addressing the unique challenges of healthcare software.
- · AI agent developers specializing in healthcare
- · Healthcare providers adopting automation
- · Patients benefiting from increased efficiency
- · Medical software companies improving integration
- · Manual clinical data entry and administrative roles
- · General-purpose AI agent benchmarks without medical specificity
Clinical computer-use agents will gain credibility and accelerate their adoption within medical institutions.
Increased automation will free up medical professionals for direct patient care, potentially improving healthcare access and quality.
The validated use of AI in medical UIs could establish new standards for AI safety and reliability across other critical sectors.
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Read at arXiv cs.AI