In healthcare, Graphiti's time-aware features deliver three core values:
Visualization of disease progression
- construct (sth abstract)Spatiotemporal Medical Record Mapping: Transform discrete test reports and medication records into a relational network with a timeline
- Example application: correlation analysis of glycemic changes and medication regimen in diabetic patients
Optimization of treatment protocols
- Differences in efficacy of similar cases identified by historical mapping comparisons
- Dynamic alerts: triggered when test indicators deviate from the developmental trajectory of similar patients
Specific implementation cases
# 构建患者节点
graph.add_node("Patient",
pid="P1002",
diagnosis="Type2_Diabetes")
# 添加时间序列检查数据
graph.add_node("LabTest",
test_date="2023-03-15",
hba1c=7.2,
fast_glucose=128)
# 建立时间关联
graph.add_edge("P1002", "HAS_TEST", "LabTest",
temporal_relation="AFTER")
# 疗效分析查询
MATCH (p:Patient)-[t:HAS_TEST]->(l:LabTest)
WHERE t.test_date > p.diagnosis_date
RETURN avg(l.hba1c)
Clinical practice has demonstrated that this program can improve physician decision-making efficiency by 301 TP3T, which is particularly suitable for chronic disease management and treatment plan evaluation.
This answer comes from the articleGraphiti: dynamic knowledge graph construction and query tool (time-aware long memory scheme)The
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