A step-by-step guide to fine-tuning MedGemma for breast tumor classification

Google's MedGemma model was successfully fine-tuned to classify breast cancer histopathology images, transforming from a general medical AI into a specialized diagnostic tool. Using the BreakHis dataset and LoRA fine-tuning techniques, the model's 8-class accuracy dramatically improved from 32.6% to 87.2%, demonstrating how foundation models can rapidly acquire specialized medical skills through targeted training.