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This query traverses the graph to return patient names and ages, demonstrating GraphDB’s ability to handle relational queries efficiently.
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## 🏗️ Architecture
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## 🧹 Architecture
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GraphDB’s modular, daemonized architecture ensures scalability, performance, and flexibility. Below is a visual representation of its components and their interactions:
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***Clinical Decision Support**: Identify drug-allergy interactions or suggest treatment paths by traversing patient history graphs in real-time. 🩺
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***Billing Optimization**: Detect missed CPT coding opportunities or fraudulent billing patterns using graph-based anomaly detection. 💰
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***Patient Risk Modeling**: Build longitudinal graphs of medical, behavioral, and socioeconomic factors for predictive analytics and proactive care. 📊
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***Patient Risk Modeling**: Build longitudinal graphs of patient medical, behavioral, and socioeconomic factors for predictive analytics and proactive care. 📊
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***Security and Compliance**: Visualize user access logs as graphs to ensure HIPAA/GDPR compliance and detect unauthorized access. 🔒
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***Research and Epidemiology**: Analyze disease propagation networks, identify clinical trial cohorts, or study social determinants of health. 🔬
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@@ -167,13 +167,15 @@ Before building GraphDB, ensure the following are installed:
@@ -245,14 +257,14 @@ The project is organized for modularity and maintainability:
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## 📦 Crate/Module Details
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### graphdb-lib 🧠
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### `graphdb-lib` 🧠
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***Purpose**: Core graph engine with data structures (nodes, edges), traversal algorithms (BFS, DFS, shortest path), and query parsing for Cypher, SQL, and GraphQL.
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***Features**:
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* Efficient in-memory graph representation.
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* Schema management for nodes and relationships.
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* Query execution engine with support for multiple query languages.
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### server 💻
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### `server` 💻
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***Purpose**: Houses the `graphdb-cli` binary for interactive and scripted use.
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***Subcomponents** (`server/src/cli/`):
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*`cli.rs`: Parses command-line arguments and dispatches commands.
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