A Scoping Review of LLM-as-a-Judge in Healthcare and the MedJUDGE Framework
As large language models (LLMs) increasingly generate and process clinical text, scalable evaluation has become critical. LLM-as-a-Judge (LaaJ), which uses LLMs to evaluate model outputs, offers a scalable alternative to costly expert review, but its healthcare adoption raises safety and bias concerns. We conducted a PRISMA-ScR scoping review of six databases (January 2020-January 2026), screening 11,727 studies and including 49. The landscape was dominated by evaluation and benchmarking applications (n=37, 75.5%), pointwise scoring (n=42, 85.7%), and GPT-family judges (n=36, 73.5%). Despite growing adoption, validation rigor was limited: among 36 studies with human involvement, the media...
| Authors | Chenyu Li, Zohaib Akhtar, Mingu Kwak et al. |
|---|---|
| Primary category | cs.CY |
| Published | 3 April 2026 |
| Last updated at source | 3 April 2026 |
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