👨‍💻AI Model Construction and Backend Logic

Architectural Patterns

• Modular AI architecture, sub-model collaboration:

  • NLP Models→ Understand the user’s intention in asking questions.

  • Medical Knowledge Graph→ Store authoritative medical and healthcare knowledge.

  • Inference Engine→ Personalized recommendations based on personal data.

Core of the conversation

• Based on the latest large language model (LLM), it is fine-tuned with male health corpus.

• Make sure your answers are both professional and relevant to the user's situation.

Quality Assurance

• Human-machine hybrid review mechanism：

  • Important health advice is reviewed by contracted doctors or senior health consultants.

  • Another set of independent AI models cross-validated the results to reduce the error rate.

Running the process

1. The user initiates a diagnosis/analysis request.

2. Using ZK zero-knowledge proof technology, the request passes authentication and permission checks (ensuring the DID/SBT is valid).

3. The AI inference module generates results.

4. The front-end returns instantly (completed in seconds).

value

• Real-time and smooth interaction.