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README.md

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+---
+license: apache-2.0
+base_model: google/medgemma-1.5-4b-it
+tags: [medical, dermatology, adverse-event-detection, medgemma]
+---
+# MedGemma AE Detection
+
+MedGemma 1.5-4B fine-tuned for **visual adverse event detection** from clinical photographs.
+
+- **Base model**: `google/medgemma-1.5-4b-it`
+- **Method**: LoRA fine-tuning (50 epochs)
+- **Task**: Classify skin AEs from patient photos into 21 categories (normal + 7 AE types × 3 CTCAE grades)
+- **AE types**: maculopapular rash, acneiform rash, periorbital edema, SJS, stomatitis, pruritus, alopecia
+
+## Usage
+
+```python
+from transformers import AutoModelForImageTextToText, AutoProcessor
+
+model = AutoModelForImageTextToText.from_pretrained("AlphaRaven/medgemma-ae-detection")
+processor = AutoProcessor.from_pretrained("google/medgemma-1.5-4b-it")
+```
+
+Part of the [Clinical Trial Simulation Engine](https://github.com/AlphaRaven/ClinicalTrialEngine) pipeline.