| --- |
| tags: |
| - medical-ai |
| - llm |
| - report-generation |
| - hallucination-detection |
| - fhir |
| - clinical-nlp |
| license: mit |
| pipeline_tag: text-generation |
| base_model: mistralai/Mistral-7B-v0.1 |
| library_name: transformers |
| --- |
| # Medical Report Generator |
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| ## Live Demo |
| 👉 [Try it on Hugging Face Spaces](https://huggingface.co/spaces/mou11/medical-report-generator) |
| ## Overview |
| An end-to-end clinical report generation pipeline that generates structured medical reports from patient data, detects hallucinations using NLI, outputs FHIR R4 compliant JSON, and exports professional PDF reports. |
| ## Results |
| | Report Type | BERTScore F1 | Safety Score | |
| |-------------|-------------|--------------| |
| | Radiology | 0.8628 | 0.625 | |
| | Discharge Summary | 0.9045 | 1.0 | |
| | Lab Report | 0.8129 | 0.375 | |
| ## Hallucination Detection |
| | Report Type | Total Claims | Hallucination Rate | Safety Score | |
| |-------------|-------------|-------------------|--------------| |
| | Radiology | 4 | 0.375 | 0.625 | |
| | Discharge | 1 | 0.0 | 1.0 | |
| | Lab | 4 | 0.625 | 0.375 | |
| ## Features |
| - Generates 3 types of clinical reports: Radiology, Discharge Summary, Lab Report |
| - Hallucination detection using NLI (cross-encoder/nli-deberta-v3-base) |
| - FHIR R4 compliant JSON output (HL7 healthcare standard) |
| - BERTScore and ROUGE evaluation metrics |
| - Professional PDF export with quality assessment table |
| - Gradio web interface |
| ## Architecture |
| Patient Data → Report Generation (LLaMA 3.3 70B via Groq) → Hallucination Detection (DeBERTa NLI) → Evaluation (BERTScore + ROUGE) → FHIR R4 JSON → PDF Export |
| ## Tech Stack |
| | Component | Tool | |
| |-----------|------| |
| | LLM | Groq — LLaMA 3.3 70B | |
| | Hallucination Detection | cross-encoder/nli-deberta-v3-base | |
| | Evaluation | BERTScore + ROUGE | |
| | FHIR Output | HL7 R4 JSON | |
| | PDF Export | ReportLab | |
| | UI | Gradio | |
| | Platform | Google Colab (T4 GPU) | |
| ## How to Run |
| 1. Get a free Groq API key at [console.groq.com](https://console.groq.com) |
| 2. Open `app.py` in Google Colab |
| 3. Add your key to Colab Secrets as `GROQ_KEY_1` |
| 4. Run all cells in order |
| ## Medical Disclaimer |
| This system is for educational and research purposes only. It does not provide medical advice. Always consult a qualified healthcare professional for medical decisions. |
| ## Project Status |
| ✅ Report generation pipeline complete |
| ✅ Hallucination detection implemented |
| ✅ FHIR R4 compliant output |
| ✅ PDF export working |
| ✅ Gradio demo deployed on Hugging Face Spaces |
