De la Anatomía al Algoritmo: Alcance de las Competencias Diagnósticas Asistidas por Inteligencia Artificial en la Educación en Ciencias de la Salud

De la Anatomía al Algoritmo: Alcance de las Competencias Diagnósticas Asistidas por Inteligencia Artificial en la Educación en Ciencias de la Salud

Contenido principal del artículo

Iván Suazo Galdames

Resumen

El artículo explora la evolución del conocimiento médico desde sus bases anatómicas y funcionales hasta la integración de herramientas tecnológicas avanzadas, con un enfoque en el impacto de la inteligencia artificial (IA) en el desarrollo de competencias diagnósticas. En sus inicios, la formación médica dependía de la observación directa y el juicio clínico basado en el conocimiento anatómico y quirúrgico. Posteriormente, la inclusión de fisiología y patologías permitió una comprensión funcional del cuerpo humano, transformando el diagnóstico en una habilidad sistemática apoyada por datos objetivos como pruebas de laboratorio e imágenes médicas. La incorporación de la IA en las últimas décadas ha revolucionado este proceso, proporcionando capacidades sin precedentes para analizar datos clínicos complejos. Herramientas como algoritmos de aprendizaje automático y sistemas predictivos han elevado la precisión del diagnóstico, permitiendo identificar patrones que antes pasaban desapercibidos. Este enfoque basado en datos refuerza la capacidad del médico para correlacionar síntomas y signos clínicos con entidades patológicas específicas. Sin embargo, la integración de la IA plantea desafíos en la educación médica. Los futuros médicos deben combinar el aprendizaje de fundamentos clínicos tradicionales con el dominio de tecnologías avanzadas, todo ello mientras mantienen un enfoque ético y centrado en el paciente. Además, la dependencia excesiva en la tecnología y los sesgos inherentes a los algoritmos subrayan la necesidad de un equilibrio entre innovación tecnológica y juicio clínico humano. El artículo destaca que la formación médica debe adaptarse para incluir competencias críticas como alfabetización digital, razonamiento ético y pensamiento crítico. Los simuladores y plataformas educativas basadas en IA están desempeñando un papel clave en la preparación de los médicos para un entorno clínico más digitalizado, mientras que la investigación sigue siendo esencial para garantizar la transparencia y equidad de estas tecnologías.

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