convaiinnovations/medgemma-4b-ecginstruct
MedGemma-4B ECGInstruct by ConvAI Innovations is a 4.3 billion parameter instruction-tuned vision-language model, fine-tuned from Google's MedGemma-4B-it. It specializes in automated 12-lead ECG interpretation, identifying cardiac abnormalities, and generating detailed clinical reports from ECG images. Trained on 1.15 million ECG image-text pairs, this model excels at vision-language instruction following for medical diagnostics.
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Overview
MedGemma-4B ECGInstruct is a 4.3 billion parameter vision-language model developed by ConvAI Innovations, fine-tuned from Google's MedGemma-4B-it. It is specifically designed for automated interpretation of 12-lead ECG images, leveraging the extensive PULSE-ECG/ECGInstruct dataset which contains 1.15 million ECG image-text pairs. The model was trained for 72 hours on 8x NVIDIA A100 GPUs, achieving a final token accuracy of 86.83%.
Key Capabilities
- Interprets 12-lead ECG images: Analyzes visual ECG data to extract clinical insights.
- Identifies cardiac abnormalities: Detects arrhythmias, ischemia, hypertrophy, and conduction blocks.
- Generates detailed clinical reports: Provides comprehensive interpretations based on ECG findings.
- Answers specific questions: Responds to queries about ECG findings, diagnosis suggestions, heart rate, and rhythm.
Intended Use
This model is suitable for:
- Research in medical AI and computer vision: A valuable tool for academic and developmental purposes.
- Educational demonstrations: Useful for teaching and learning ECG interpretation.
- Development of clinical decision support prototypes: Can serve as a component in early-stage medical software development.
Limitations
- Primarily trained on adult ECG data; performance on pediatric ECGs may vary.
- NOT validated for clinical use and should not replace professional medical diagnosis. It is for research and educational purposes only.