| --- |
| license: other |
| license_name: commercial-license |
| license_link: LICENSE |
| tags: |
| - code |
| - healthcare |
| - clinical |
| - emr |
| - spring-boot |
| - react |
| - java |
| - typescript |
| - production |
| - ai-training |
| - llm-training |
| - microservices |
| - pull-requests |
| size_categories: |
| - 100K<n<1M |
| task_categories: |
| - fill-mask |
| - text-generation |
| pretty_name: Production Clinical EMR Codebase — AI Training Data | Java Spring Boot React |
| language: |
| - en |
| --- |
| |
| # Clinical EMR Platform Codebase |
|
|
| **Production-grade clinical platform codebase available for commercial AI training licensing.** |
|
|
| ## Overview |
|
|
| This dataset contains the full source code of a production electronic medical records (EMR) and clinical management platform, built and deployed over 27 months with real doctors across 40+ medical specialties. |
|
|
| The codebase is available as a **non-exclusive commercial license** for AI model training, fine-tuning, and benchmarking purposes. |
|
|
| ## What Makes This Valuable for AI Training |
|
|
| **Real engineering history — not synthetic code.** |
| - 6,267 commits over 27 months of active development |
| - 2,381 pull requests averaging 203 lines of code each — real code review decisions, revisions, and approvals made under production conditions |
| - 18 unique contributors |
| - 2,565 source files across 31 repositories |
|
|
| **Domain specificity.** |
| Specialty-specific clinical decision logic across 40+ medical specialties including psychiatry, obstetrics and gynecology, and pediatrics. Rule-based medication suggestion engines, emergency alert triggers, and patient intake flows built to real clinical standards. |
|
|
| **Production validation.** |
| This code was deployed to 150+ paying doctors who used it for real clinical workflows. It has been tested against real-world cases |
|
|
| ## Technical Specifications |
|
|
| | Metric | Value | |
| |---|---| |
| | Total Lines of Code | 338,607 | |
| | Repositories | 31 | |
| | Commits | 6,267 | |
| | Pull Requests | 2,381 | |
| | Avg PR Lines | 203.6 | |
| | Unique Contributors | 18 | |
| | Development Period | 27 months | |
| | Source Files | 2,565 | |
| | Dependencies | 393 packages | |
|
|
| ## Language Composition |
|
|
| | Language | Lines | Share | |
| |---|---|---| |
| | JavaScript | 213,924 | 63.2% | |
| | Java | 87,979 | 26.0% | |
| | TypeScript | 34,004 | 10.0% | |
| | Python | 2,565 | 0.8% | |
|
|
| ## Stack |
|
|
| Spring Boot · React · Next.js · Java · TypeScript · Python · SQL |
|
|
| ## Use Cases |
|
|
| - Fine-tuning coding LLMs on domain-specific enterprise Java and React |
| - Training code review and code synthesis models using real PR history |
| - Benchmarking coding agents on clinical/healthcare domain code |
| - Building healthcare-specific coding assistants |
|
|
| ## Licensing |
|
|
| This dataset is available under a **commercial non-exclusive license**. |
|
|
| - Licensor retains full IP ownership |
| - Buyer receives perpetual non-exclusive rights for AI training use |
| - Multiple licenses available — non-exclusive means you are not the sole licensee |
|
|
| **This dataset is gated. To request access, contact:** |
|
|
| mithun@swingbell.com |
|
|
| Please include your organisation name, intended use case, and estimated training scope in your request. |
