Enhancing Clinical Decision Support and Patient Communication Using MedGemma and Open Health AI Models

Abstract This research presents an intelligent healthcare application built using MedGemma and open Health AI Developer Foundation models to enhance clinical workflows, patient communication, and decision support. The study explores how domain-specific large language models can accurately interpret medical text, summarize patient information, and assist healthcare professionals in making informed decisions while maintaining safety and transparency. Using real world medical text datasets, the system is evaluated for contextual understanding, response relevance, and practical clinical usefulness. Results demonstrate that MedGemma-based solutions can significantly reduce documentation burden, improve information accessibility, and support patient centered care, highlighting the growing role of open medical AI models in modern digital healthcare systems.