SELARAS

Transitioning intricate clinical methodologies into an accessible digital solution presents a significant technical hurdle. The primary challenge lies in seamlessly integrating the European Society of Cardiology’s SCORE2 risk calculation algorithm with a dynamic user assessment, ensuring complex medical metrics are computed instantaneously and accurately without degrading client-side performance. Furthermore, architecting a reliable data pipeline to process user inputs through PHP while concurrently prompting Google Gemini AI to generate contextual, easy-to-understand lifestyle recommendations demands precise state management and absolute type safety.

To overcome these complexities, the platform’s frontend was engineered using TypeScript and React to build a dynamic, fluid questionnaire system backed by real-time risk scoring. Interactive data visualization charts were integrated to smoothly transform structured clinical results into intuitive health trend overviews for the user. By offloading the core algorithmic data handling to a robust PHP backend and implementing an asynchronous connection to the Google Gemini API, the architecture effectively translates heavy medical telemetry into highly personalized, responsive prevention insights.