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Consenso de expertos sobre la lista de competencias de aptitud en inteligencia artificial y el marco de evaluación
Meng-Chun Gong1, Hui Pan2, Hui Liu3
1Guangdong Medical University,Dongguan,Guangdong 523808,China.
Resumen
Este consenso describe una lista de competencias de alfabetización en inteligencia artificial (IA) y un marco de evaluación para estudiantes de medicina. Su objetivo es preparar a los futuros profesionales de la salud para un panorama médico impulsado por la IA.
Área de la Ciencia:
- Educación Médica
- Inteligencia Artificial en la Atención Médica
- Educación Basada en Competencias
Sus antecedentes:
- El rápido avance de la atención médica inteligente exige la formación de profesionales médicos con alfabetización en IA.
- Los marcos de educación médica existentes requieren adaptación para integrar las competencias de IA.
- La educación médica basada en competencias (EMBC) proporciona una base para el desarrollo de médicos preparados para la IA.
Objetivo del estudio:
- Desarrollar una lista integral de competencias de alfabetización en IA para estudiantes de medicina.
- Establecer un marco de evaluación práctico para evaluar las competencias de IA en la educación médica.
- Guiar a las facultades de medicina en la integración de la IA en sus planes de estudio para la atención médica inteligente.
Principales métodos:
- Método Delphi de dos rondas que involucra a un panel multidisciplinario de expertos.
- Revisión sistemática de la literatura para informar el desarrollo de competencias.
- Integración de modelos de competencias y la pirámide de competencia clínica de Miller.
Principales resultados:
- Una lista de competencias de alfabetización en IA de 21 indicadores para estudiantes de medicina, categorizada en conocimiento (8), habilidades (8) y actitudes (5).
- Un sistema de evaluación propuesto que incluye pruebas estandarizadas, pruebas de juicio situacional y exámenes clínicos objetivos estructurados basados en escenarios de IA.
- Una estrategia de evaluación longitudinal recomendada en las fases de admisión, preclínica y clínica.
Conclusiones:
- La lista de competencias de IA y el marco de evaluación desarrollados poseen rigor científico y aplicabilidad práctica.
- Este consenso sirve como una referencia crucial para las facultades de medicina que integran la IA en la educación.
- Apoya el cultivo de talentos médicos compuestos para la era de la atención médica inteligente.
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