Physical examinations are an important part of our health care, but among many medical examination items, it is often difficult to understand the meaning and correlation of various indicators. In order to help you better understand the results of the physical examination, I will introduce a professional and interesting physical examination knowledge map system development scheme.
1. System overview
The physical examination knowledge graph system is an intelligent system based on the medical knowledge graph, which aims to help users better understand the results of physical examination, understand the risk of related diseases, and provide personalized health suggestions and recommendations.
Second, the composition of the system
1. User Health Information Base:
- Abnormal sign database: including medical abnormal data and abnormal data during the time period, recording the abnormalities detected by the user through medical instruments and the abnormalities during self-examination.
- User personal information: including basic information, life behavior information and itinerary information, which is used to establish user health portraits.
2. Medical Knowledge Graph:
- Based on the knowledge map of the medical field, including diseases, symptoms, examination items, etc., it is used to analyze the results of physical examinations and provide health advice.
Third, the system workflow
1. Data collection and modeling:
- Collect users' medical examination data and personal information, and establish a user health information database.
- Build a medical knowledge graph and integrate relevant knowledge in the field of medicine.
2. Anomaly analysis:
- Based on the user's physical examination data and personal information, establish the user's health profile through medical abnormal data and abnormal time period data.
- Analyze the occurrence time and correlation of anomalies, and set anomaly category characteristic labels.
3. Health Recommendations and Recommendations:
- Recommend relevant health items and suggestions based on the user's abnormal situation and life behavior information within the relevant time period, combined with the medical knowledge graph.
- Establish occupational category health profiles based on the user's occupation, age and regional characteristics, and assess the health risks of abnormal situations.
Fourth, the system advantages
1. Personalized recommendation: Provide personalized health suggestions and recommendations based on users' personal information and abnormal conditions to help users better manage their health.
2. Knowledge graph support: Based on the medical knowledge graph, the system can analyze the physical examination results, provide relevant disease risk assessments, and give corresponding suggestions.
3. Data analysis ability: By analyzing the user's abnormal situation and life behavior information within the relevant time period, the system can more accurately assess health risks.
Epilogue:
The physical examination knowledge graph system is an intelligent health management tool that helps users better understand physical examination results, understand health risks, and provide personalized health suggestions and recommendations by integrating medical knowledge and users' personal information. I believe that in the future, such a system will become a powerful assistant for our health management.