Learning Graph Quality Analysis
Overall Quality Score
Score: 90/100
Rating: Excellent
✓ The learning graph meets quality standards and is ready for use.
Basic Statistics
- Total concepts: 200
- Concepts with dependencies: 196
- Foundational concepts (no dependencies): 4
- Total dependencies: 299
- Average dependencies per concept: 1.50
- Maximum dependency chain length: 11
DAG Structure Validation
✓ PASS: The graph is a valid Directed Acyclic Graph (no cycles detected).
Self-Dependency Check
✓ PASS: No self-dependencies detected.
Foundational Concepts
Found 4 foundational concepts (2.0%):
- Concept 1: Graph Theory Basics
- Concept 13: Relational Database
- Concept 16: Healthcare System
- Concept 161: Artificial Intelligence
Orphaned Nodes (Leaf Concepts)
Found 87 orphaned concepts (43.5%):
- Concept 7: Edge Property
- Concept 18: Per-Person Healthcare Cost
- Concept 31: Clinical Workflow
- Concept 32: Patient Demographics
- Concept 35: Healthcare Data Exchange
- Concept 37: GQL Standard
- Concept 38: GSQL
- Concept 42: Query Performance
- Concept 43: Path Query
- Concept 44: Subgraph Query
- Concept 45: Aggregate Query
- Concept 47: Patient ID
- Concept 48: Patient History
- Concept 50: Medical Condition
- Concept 56: Dosage
- Concept 57: Drug Interaction
- Concept 58: Adverse Event
- Concept 59: Allergy
- Concept 60: Immunization
- Concept 62: Lab Result
- Concept 63: Vital Sign
- Concept 66: Patient Journey
- Concept 67: Chronic Disease Management
- Concept 68: Preventive Care
- Concept 70: Quality of Life Metric
- Concept 75: Outpatient Facility
- Concept 76: Inpatient Care
- Concept 77: Emergency Department
- Concept 80: Appointment
- Concept 83: Medical License
... and 57 more
Top 10 Most Depended-Upon Concepts
Concepts with the highest indegree (most other concepts depend on them):
| Rank | Concept ID | Concept Label | Indegree |
|---|---|---|---|
| 1 | 22 | Healthcare Provider | 13 |
| 2 | 16 | Healthcare System | 9 |
| 3 | 146 | Graph Algorithm | 9 |
| 4 | 96 | Insurance Claim | 8 |
| 5 | 4 | Graph Database | 7 |
| 6 | 12 | Graph Query | 7 |
| 7 | 23 | Healthcare Patient | 7 |
| 8 | 46 | Patient Record | 7 |
| 9 | 1 | Graph Theory Basics | 6 |
| 10 | 131 | Healthcare Fraud | 6 |
Recommendations
- High number of orphaned nodes (43.5%). Consider if capstone/final concepts should have more concepts building upon them.
- Overall, the graph structure is good and ready for taxonomy assignment.
Report generated by analyze-graph.py