Integration of multidimensional health data for applications
The system's core competency lies in the integration of three key types of health data: whole genome sequencing results (covering 5,000+ common SNP loci), 200+ clinical laboratory test metrics, and a medically validated database of 3,000+ supplements. This fusion of multiple sources of data allows recommendations to take into account both innate genetic factors and current physiological status.
- Genetic data is modeled using Polygenic Risk Score calculations
- Laboratory data to support dynamic trend analysis
- Supplement database includes evidence-based medical grade labeling
In a typical application scenario, the system cross-analyzes the user's MTHFR gene variant and homocysteine test values to give a personalized folic acid supplementation regimen. This data-driven approach allows for a clinical guidance level of recommendation accuracy.
This answer comes from the articleRAG-based construction of a mini-assistant providing health advice (pilot project)The
