Data Characteristics
Home medical device registration documents primarily source data from regulatory files, technical standards, clinical trial reports, product manuals, risk management reports, test reports, and manufacturing process documents. Document update frequency is influenced by policy adjustments and product iterations, typically quarterly or annually. However, core technical standards and regulatory revisions can trigger ad-hoc updates. Regulatory documents often feature hierarchical clauses. Technical reports contain numerous charts, specialized terminology, and units of measurement. Fields include product model, performance indicators, scope of application, contraindications, usage instructions, maintenance, and safety warnings. Performance indicators often include specific numerical ranges and units, such as V (Volts), mA (milliamperes), ℃ (Celsius), and mmHg (millimeters of mercury). Data typically exists as PDFs, Word documents, or scanned images.
Constraints on Knowledge Base Retrieval and Recall
The characteristics of home medical device registration documents pose specific challenges for knowledge base retrieval and recall. The rigor and nested structure of regulatory clauses require the knowledge base to accurately identify text hierarchy, preventing misinterpretation. Technical reports with charts and specialized terminology imply that pure text retrieval may be insufficient, necessitating stronger semantic understanding to link chart content with textual descriptions. Frequent updates demand efficient incremental indexing and version management capabilities to ensure retrieval timeliness. Furthermore, numerical ranges and units for performance indicators, such as 100-240V or 0.5-2.0A, require support for numerical range queries and unit conversion during retrieval. This prevents recall omissions due to inconsistent units or imprecise numerical range matching. The presence of scanned documents emphasizes reliance on OCR quality and subsequent text processing capabilities.
Configuration Settings
| Configuration Item | Suggested Value | Rationale |
|---|---|---|
Chunk size (Segment Length) | 500–800 characters (characters) | Ensures completeness of regulatory clauses and technical details, preventing truncation of key information. |
Chunk Overlap Length (Segment Overlap Length) | 100–150 characters (characters) | Maintains contextual coherence, especially when providing sufficient background for cross-paragraph references. |
Recall count (Recall Count) | 8–12 entries (segments) | Given the complexity of declaration documents, provides more relevant snippets for the model's comprehensive judgment. |
Similarity threshold (Similarity Threshold) | Calibrated by actual measurement 0.75–0.85 | Balances recall rate and accuracy, ensuring highly relevant documents are included. |
Rerank result count (Reranked Return Count) | 5 entries (segments) | Focuses on the most relevant core information, reducing the burden on the model to process irrelevant content. |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds (seconds) | Handles large PDF and Word documents, particularly reports containing complex charts and tables. |
Common Pitfalls
- Retrieval results contain numerous irrelevant or low-relevance regulatory clauses. This occurs when the segmentation strategy is too coarse, failing to effectively differentiate regulatory hierarchies.
- The model cannot accurately answer questions involving device performance parameters, such as specific voltage or current ranges. This happens when the knowledge base fails to effectively extract and index numerical data, preventing numerical range matching during retrieval.
- When processing reports from scanned documents, retrieval results show garbled text or missing key information. This is due to poor OCR quality or insufficient subsequent text cleaning.
Verification of Configuration
- Select multiple typical query questions, such as "What are the contraindications for XX model home ventilator?" or "What are the safety requirements for power adapters in XX regulation?". Check if the recall results include all relevant and accurate regulatory clauses or technical descriptions.
- For queries involving performance parameters, such as "What is the measurement accuracy range of a blood glucose meter?", verify that the recall results correctly match numerical ranges and units.
- Regularly upload newly published regulations or product update documents. Check the knowledge base's indexing update speed and the retrieval recall effectiveness of new documents.
- In the knowledge base management interface, check the parsing status of complex documents (e.g., large PDF reports) to confirm no parsing failures or timeouts occurred.
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.