Healthcare / Life Sciences

Medical Literature Review AI Architecture

Compare RAG, fine-tuning, long-context, and hybrid approaches for medical literature review at 10K queries/month.

Top approaches

#1 Best fit

Hybrid / RAFT

Clinical terminology + citation accuracy both required.

#2 Runner-up

RAG

Correct for most use cases; simpler to audit.

#3 Alternative

Fine-Tuning

Only for terminology normalisation sub-tasks.

Estimated at 10K queries/month

Long-Context$202/mo

RAG$322/mo

Hybrid / RAFT$3,314/mo

Fine-Tuning$4,987/mo

1All outputs must be clearly labelled as AI-assisted; require physician review.
2Use HIPAA-compliant infrastructure for any patient-linked data.
3Evaluate on MIMIC or a held-out clinical trial dataset before production deployment.

回答 9 个问题 — 用 Medical Literature Review 默认值预填 — 以获得确定性架构推荐、成本交叉图和 8 页 PDF 报告。