Data Characteristics for This Category
Quality documents related to respiratory system diseases originate from diagnostic and treatment guidelines, clinical pathways, drug inserts, medical guidelines from various medical institutions, and approval documents and quality standards published by national drug regulatory bodies. Update frequencies for these documents vary. Clinical guidelines may update every 2–5 years, while drug inserts or approvals change dynamically based on pharmaceutical company submissions and approval processes. Document structures are primarily PDF, Word, or structured XML formats. They contain extensive medical terminology, laboratory indicators, dosage units, diagnostic codes (e.g., ICD-10), and treatment flowcharts. Drug dosages are often precise to milligrams (mg) or micrograms (µg), and time units involve hours, days, and weeks.
Constraints Imposed by These Characteristics on Citation and Traceability
Inconsistent document update rhythms require the knowledge base to clearly label the version and publication date of cited content to avoid referencing outdated information. Complex document structures, especially flowcharts and tables, demand high-quality text extraction and segmentation to ensure the integrity and contextual relevance of cited sources. The specialized and precise nature of medical terminology means that similarity calculations must incorporate semantic understanding to prevent misjudgments due to synonyms or near-synonyms. Additionally, critical data in approvals and inserts (e.g., dosages, indications) must be precisely traceable to specific paragraphs or tables in the original documents to meet compliance requirements.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
Chunk size (Segment Length) | 300–500 characters | Ensures the completeness of medical concepts and prevents critical information from being split. |
Recall count (Recall Count) | Top 8–12 entries | Covers a sufficient number of potentially relevant knowledge points, especially when multiple disease factors or drug interactions are involved. |
Similarity threshold (Similarity Threshold) | Calibrate based on actual measurements | Requires adjustment based on the specific dataset's medical terminology and document quality to balance recall and accuracy. |
Rerank result count (Reranked Return Count) | Top 5 entries | Prioritizes the display of the most relevant authoritative diagnostic and treatment evidence, reducing interference from irrelevant information. |
maxContext | 4096 tokens | Ensures the model has sufficient contextual understanding to process complex medical case descriptions and multi-document references. |
UPLOAD_FILE_MAX_SIZE | 200 MB | Accommodates the file size of medical guidelines and drug inserts, which often contain numerous charts and flowcharts in PDF format. |
Three Common Pitfalls
- Viewing the full response outputs many seemingly irrelevant citations because the
Similarity threshold(Similarity Threshold) is set too low, leading to the recall of numerous weakly related or generic medical concepts. - Web links from knowledge base sources (e.g., Notion) cannot be parsed correctly because the system's default file parser does not support direct crawling and conversion of content from specific platform links.
- When citing specific drug dosages or laboratory indicators, the response content lacks critical numbers or units. This occurs when the document segmentation strategy fails to effectively identify and retain the association between numbers and units, leading to context fragmentation.
How to Confirm Correct Configuration
- For typical respiratory system disease queries, check if the cited document sources in the response include the latest clinical guidelines, drug inserts, and relevant approvals, and verify their version information.
- Randomly select multiple responses and compare the cited content with the corresponding paragraphs in the original documents to confirm the accuracy and completeness of the cited text.
- Input questions involving precise information such as drug dosages or diagnostic standards. Verify that the response can accurately provide specific numerical values and units, and trace them back to their exact location in the original document.
Note: The values provided are common starting points. They should be measured against specific samples.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-21.