Data Characteristics
Cardiovascular intervention regulations and SOP documents originate from national health commissions, medical device regulatory agencies, industry associations, and hospital internal operating procedures. These documents are typically in PDF, Word, or scanned image formats, with varying degrees of structure. Update frequency is relatively stable; national guidelines are revised every few years, while hospital SOPs are adjusted annually or semi-annually based on equipment updates, technological advancements, or clinical feedback. Document content covers the entire process, from device procurement, storage, pre-operative preparation, intra-operative details, post-operative management, to complication handling. Key fields include device model, operating steps, risk level, indications, contraindications, dosage units (e.g., mg, ml), time units (e.g., seconds, minutes), and pressure units (e.g., mmHg).
Constraints on Model Integration and Configuration
The update frequency of cardiovascular intervention regulatory documents necessitates regular incremental updates or full reconstruction of the knowledge base. The presence of PDFs and scanned images demands high document parsing capabilities, ensuring accurate OCR recognition and complete structural analysis. Documents contain numerous specialized terms, abbreviations, and numerical data, requiring the model to accurately identify this information during semantic understanding to avoid errors due to contextual misinterpretation. For example, for numerical values with units like "balloon expansion pressure," the model must correctly extract and use them in logical judgments. Additionally, different sources may have varying phrasing, requiring the model to possess knowledge fusion and conflict resolution capabilities to ensure authoritative and consistent answers.
Configuration Guidelines
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
Chunk size (Chunk Size) | 800–1200 characters | Ensures each chunk contains sufficient contextual information for the model to understand complex operating procedures and regulatory details. |
Recall count (Recall Count) | 8–12 entries | Considering the complexity and cross-referencing in regulatory documents, increasing the recall count improves the coverage of relevant information. |
Similarity threshold (Similarity Threshold) | 0.78–0.85 | Sets a higher similarity threshold for specialized terms and normative statements, filtering out irrelevant or generalized content. |
Rerank result count (Reranked Return Count) | 3–5 entries | Focuses on the most relevant and authoritative regulatory provisions, preventing users from being overwhelmed by excessive redundant information. |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Provides ample file parsing time when processing large PDFs or scanned images, preventing import failures due to timeouts. |
maxContext | 3000 Tokens | Accommodates the complex context of long process descriptions and multi-condition judgments in cardiovascular intervention SOPs, ensuring the model can handle longer inputs. |
Common Pitfalls
- Symptom: Model answers contain incomplete terms or numbers, such as "pressure" without a unit. Reason: Document chunks are too short, or the parsing failed to correctly identify and associate unit information within the context.
- Symptom: Uploading large regulatory PDF files results in a prolonged system unresponsiveness or
Api response error. Reason:PARSE_FILE_TIMEOUT_SECONDSis set too low, insufficient to handle the computational load of file parsing. - Symptom: The model's answer for an operating step does not match the latest revised SOP. Reason: The knowledge base was not updated in a timely manner, or effective version management was not applied during the import of old and new document versions.
Verification of Configuration
- Select core SOPs in the cardiovascular intervention field. Ask questions about device models, key operating steps, and complication handling. Check if answers are accurate, complete, and cite the correct original regulations.
- Import a batch of scanned documents containing tables and diagrams. In the knowledge base chunk preview, check if key information (e.g., device parameters, flowchart text descriptions) is correctly recognized and extracted.
- Test the model's ability to handle questions regarding differences between new and old versions of regulations. Confirm the model prioritizes the latest version and can explain changes between versions.
The values provided are common starting points and should be measured against the reader's own 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.