For eB2 MindCare, information collection, data quality, and the internal treatment process are vital. As digitalization has advanced, data has become more distributed and fragmented. Additionally, data generation is faster over time and requires constant updates.

Integrating artificial intelligence into a mental health monitoring system is crucial for improving data quality and, consequently, the system’s effectiveness at each stage of its value chain. By doing so, it enhances data capture, processing, and analysis, boosts personalized predictions and early detection, and ensures a more efficient experience for users (patients, therapists, and family members). Furthermore, AI can reduce bias, automate processes, and provide valuable insights that aid in the continuous improvement of the system, resulting in a more precise, timely, and scalable approach to mental health care through eB2 MindCare.

This project improves the data capture process and automates it, which will lead to a better quality of treated data and, therefore, a higher quality of indicators and predictions obtained from them.