Aplicación móvil de Diagnóstico Médico Asistido por Inteligencia Artificial como Apoyo en Contextos con Acceso Limitado

In contexts with limited access to healthcare services, mobile technologies can facilitate preliminary medical guidance. This article presents an AI-assisted mobile application that allows users to enter symptoms, upload clinical images, and receive a preliminary diagnosis with a suggested medical specialty. The system combines natural language processing and image interpretation using a multimodal AI model. The architecture includes an interface developed in Android Studio, an API in .NET 8, and a cloud database. It was evaluated using 50 simulated clinical cases and 1,850 real consultations over a three-week period. The results achieved a diagnostic accuracy of 92% and an average response time of 2.9 seconds. These indicators validate its functionality and reliability as an initial clinical support tool. The solution offers high potential for reducing diagnostic delays and improving access to medical care in vulnerable communities.