This capstone project, conduxted in collaboration with the Okanagan College Computer Science Department, involves developing a cross-platform mobile application that leverages a Large Language Model (LLM) trained with curated healthcare data. The app will enable users to ask health-related questions and receive responses based on the LLM’s trained data.

The project developed for both Android and iOS, utilizing modern frameworks to ensure cross-platform compatibility. The app will integrate user authentication, allows access to healthcare data stored on mobile devices, and facilitate seamless distribution via the respective App Stores.

We are very happy to have the initail steps towards expanding secure, custom trainied Effie LLm to the mobile space including auido support.

Main Objectives:

1. Develop a mobile healthcare app compatible with both Android and iPhone platforms. Effie showcases its ability to provide continuous health monitoring, allowing patients to receive personalized health insights and alerts, thereby improving patient engagement and outcomes.
2. Leverage a custom healthcare-focused LLM API to provide accurate health-related responses.
3. Implement a database to store user interactions, medical history, and preferences.
4. Access and utilize healthcare data stored on the user's mobile device, such as health apps or files.
5. Ensure compliance with healthcare regulations (e.g., HIPAA).