K-Health enhances its AI physician by fine-tuning Gemma 3 with real-world clinical data - deepmind.google
K Health is revolutionizing patient care by refining its AI physician, Gemma 3, using real-world clinical data to improve conversational capabilities. By leveraging a 24/7 virtual primary care platform, K Health provides accessible services such as urgent care, chronic condition management, medical weight loss, and mental health support.
To enhance patient intake processes, K Health migrated its AI model to Gemma 3 on Google Cloud's Vertex AI, which reduced inference costs while boosting service personalization. The existing intake chat system proved less conversational and empathetic, prompting the team to aim for an interaction style that felt more professional.
The solution involved employing smaller, well-tuned AI models over larger ones, prioritizing decision-making logic training rather than simple content generation. After thorough evaluations, the team selected Gemma 3 for its balance of performance and cost. They implemented a structured training framework using multi-node GPU clusters, allowing for efficient scaling of model variants.
Direct preference optimization (DPO) was utilized to refine conversation quality based on accuracy, coherence, and clinical outcomes like referrals or prescriptions. The DPO training notably improved the Gemma 3 4B model’s performance score from 0.48 to 0.76, affirming the team's hypothesis that smaller models, when finely tuned, can outperform larger domain-specific variants.
Additionally, the team utilized Axolotl AI with Accelerate in a custom multi-node setup, significantly slashing training time by two-thirds while achieving 90-95% model accuracy. These innovations reduced API call numbers per chat, leading to increased efficiency and lower operational costs. As a result of these advancements, K Health’s AI physician now offers a more natural conversational experience, underscoring the potential of AI in enhancing clinical interactions and patient care outcomes.


