Features Overview

Home page offers five entry categories—Basic, Nutrition, Mental Health, Fitness, and Clinic—for compiling user health profiles that cover over 30 distinct health assessment parameters. These profiles form a comprehensive knowledge base, providing training data for the LLM. Through domain-specific fine-tuning, the model delivers contextually relevant and personalized health-related responses.

Health assessment algorithms in EasyHealth AI rely on scientific scales, including the Hospital Anxiety and Depression Scale and the World Health Organization’s Healthy Diet Indicator. The platform continuously integrates insights and research findings with each update.

EasyHealth AI adopts a conversational interface paradigm, featuring an AI-driven health assistant designated as “Yi.” This design facilitates natural, message-based interactions, credible access to personalized health information through an AI-powered interface. Conversations are structured around evidence-based health insights, strategies, and interventions across multiple health domains.
The AI assistant responds to user-input queries with customized text responses. Available 24/7 for immediate health information access, the assistant meets users’ health needs on-demand, enhancing information access and providing emotional support through interactive engagement. A multi-turn dialogue mechanism allows users to explore health topics in depth, promoting better understanding and acceptance of health information.

EasyHealth integrates sophisticated algorithms for emotional intelligence processing, health record management, health assessment, and personalized consultations. Emotional intelligence processing features AI response style customization, with the chatbot Yi able to understand and adapt to different communication styles, dynamically adjusting its language style. Empathic responses are calibrated to the user’s mood, and the smart Q&A page offers a “Customize message personally” option, allowing users to tailor how responses are generated.
Personalized consultation engines include therapeutic elements such as content personalization based on interaction history, preference-aware adaptations, feedback-driven content optimization, and continuous database updates based on user interactions.