UroScribe — Fine-tuned Medical Vision-Language Model

A fine-tuned version of MedGemma-4B specialized for automated urology ultrasound report generation.

Model Description

UroScribe takes a urology ultrasound image as input and generates a structured, clinically formatted radiology report. It was fine-tuned to bridge the gap between raw imaging and the time-consuming process of manual report writing in urology practice.

Base Model

• Architecture: MedGemma-4B (vision-language)
• Fine-tuning method: QLoRA (4-bit quantization + LoRA adapters)
• Training hardware: NVIDIA H200

Intended Use

• Automated structured report generation from urology ultrasound images
• Clinical decision support tooling
• Research into medical vision-language models for subspecialty radiology

Input / Output

Input: Urology ultrasound image (PNG)
Output: Structured radiology report including findings, impressions, and recommendations

Limitations

This model is intended for research and demonstration purposes only. It is not FDA-cleared and should not be used for clinical decision-making without physician oversight.

Developed By

Built during Hacklytics 2026 by Benito Karkada & Hadi Malik.