AI-EMR Yejin Clinic

Project Overview

An AI-assisted electronic medical record system for Korean medicine clinics

Yejin digitizes clinical records and prescription-support workflows for Korean medicine clinics. The implementation covers the frontend, AWS backend, and deployment structure, with particular attention to per-clinic data isolation, user permissions, and clinical-data access patterns.

Key Implementations

• Clinical-record UI: Build patient and encounter flows plus a prescription-support interface with React and TypeScript
• Multi-tenant identity: Define per-clinic user and authorization boundaries with AWS Amplify Gen1 and Cognito
• Data isolation: Design DynamoDB keys around clinic, patient, and encounter access patterns
• GraphQL API: Shape queries and responses around the clinical data required by each workflow
• Serverless backend: Run APIs and prescription-support logic in Lambda
• Infrastructure as code: Manage environments and deployment configuration through CloudFormation

Technical Architecture

1. Frontend & Auth

• ReactJS · TypeScript: EMR UI and prescription-support interface
• AWS Amplify Gen1: Multi-tenant application configuration
• Cognito: User authentication and authorization

2. Backend & Data

• Lambda · GraphQL: APIs and prescription-support logic
• DynamoDB: Access-pattern-driven key design and per-clinic data boundaries
• CloudFormation: Infrastructure as code and deployment automation

Key Technologies

ReactJS, TypeScript, AWS Amplify Gen1, Lambda, DynamoDB, GraphQL, Cognito, CloudFormation

Developed with React, AWS Amplify Gen1, and an AI-assisted EMR workflow for Korean medicine clinics.