Cancer registries are essential for population-level surveillance, epidemiologic research, and public health planning, but their accuracy depends on human review of key variables documented in unstructured clinical text. This is time-consuming, and current quality assurance (QA) typically relies on reviewing fewer than...
M. Seifaddini, M. Beheshti, J. Steffens et al.· medRxiv· 0 citations
Domain-specific RAG improved evidence grounding and response quality for cancer registry questions while enabling citation-supported assistance across complexity levels, and demonstrates the potential of human-centered, citation-grounded AI to support cancer registrars while preserving human oversight for final coding...
Vani Seth, M. Beheshti, Anirudh Kambhampati et al.· 0 citations
Overall, the evidence suggests that success in lower capability levels does not consistently translate to higher-level reasoning, especially when reports are inconsistent, required staging inputs are missing, or clinical assumptions must be inferred, which helps explain gaps between benchmark results and practical adop...
Maryam Seifaddini, Mohammad Beheshti, Steven Richberg et al.· Modern Pathology· 0 citations
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