Design of a graphical interface for capturing, analyzing, and visualizing data using AI in psychiatry

Abstract

This article presents the development of an intelligent graphical interface that collects, analyzes, and visualizes data relevant to psychiatry in order to overcome current barriers to reliable and up-to-date information. Data dispersion, lack of standardization, and the presence of inconsistent information hinder both scientific research and clinical care. This project, driven by a research group, proposes a technological solution based on artificial intelligence that incorporates advanced data cleaning, normalization, and validation processes.

The platform integrates information from multiple sources, such as scientific studies, medical databases, and social media publications, enabling the identification of trends, emerging treatments, and recent clinical studies. To ensure data quality, filtering and error correction techniques are applied, removing duplicates and completing incomplete records. Additionally, an intuitive and accessible interface was developed, validated through rigorous usability, module integration, and data accuracy testing.

The result is a powerful tool for researchers, health professionals, and the general public, facilitating informed decision-making and promoting a more aware society regarding mental health. This project has the potential to become a reference for the scientific and medical community, driving significant advances in the diagnosis, treatment, and prevention of mental disorders.