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Publicado el 20 de noviembre de 2025 | http://doi.org/10.5867/medwave.2025.10.3120

Inteligencia artificial para la clasificación y el diagnóstico de lesiones cutáneas en dermatología: una revisión narrativa

Artificial intelligence for skin lesion classification and diagnosis in dermatology: A narrative review

Paula Andrea Ramos Chaparro, Erwin Hernando Hernández Rincón , Nicolas Melo Sierra, Gabriela Alejandra Osorio Betancourt, Diana Marcela Díaz Quijano, Samuel David Barbosa Ardila, Mariam Rolón Cadena, Alejandro Rueda Rodríguez

Resumen

Introducción La inteligencia artificial (IA) tiene una presencia cada vez mayor en dermatología, demostrando niveles de precisión comparables o incluso superiores a los de los dermatólogos en el diagnóstico de lesiones cutáneas a partir de imágenes clínicas y dermatoscópicas. Esta revisión ofrece una visión general del papel de la IA en la clasificación automatizada y el seguimiento de las lesiones cutáneas.

Objetivo Explorar y cartografiar la literatura existente sobre el uso y los beneficios de la IA en dermatología.

Métodos Esta revisión narrativa se centró en el uso y las ventajas de la IA en dermatología, utilizando los términos MeSH/DeCS: "Dermatology", "Artificial Intelligence", "Diagnosis" y "Computer Aided Diagnosis". Se consultaron tres bases de datos (PubMed, LILACS y Scopus) para el periodo comprendido entre 2008 y 2024. Se excluyeron los estudios que no se enfocaban en dermatología, carecían de relación con inteligencia artificial o presentaban diseños teóricos sin aplicación práctica ni evidencia, lo que permitió obtener una selección final de cuarenta y cuatro artículos.

Resultados Los hallazgos respaldan sólidamente la efectividad de la IA y evidencian una precisión diagnóstica comparable o superior a la del dermatólogo humano en diversas tareas. La evolución de la IA en dermatología indica una transformación sustancial en la atención, ampliando sus aplicaciones desde el cáncer de piel hasta diversas patologías dermatológicas. Si bien se destaca la importancia de la colaboración entre la IA y los profesionales de la salud, persiste una brecha crítica en la validación clínica de la IA en contextos reales. Además, las consideraciones éticas, especialmente en la toma de decisiones automatizadas, requieren una atención rigurosa.

Conclusiones Esta revisión narrativa resalta el papel fundamental de la IA en dermatología, y subraya su capacidad para mejorar la precisión diagnóstica de las lesiones cutáneas.

Esta obra de Medwave está bajo una licencia Creative Commons Atribución-NoComercial 3.0 Unported. Esta licencia permite el uso, distribución y reproducción del artículo en cualquier medio, siempre y cuando se otorgue el crédito correspondiente al autor del artículo y al medio en que se publica, en este caso, Medwave.

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Autores

Paula Andrea Ramos Chaparro

Universidad de La Sabana, Chía, Colombia

https://orcid.org/0009-0003-0269-291X

Erwin Hernando Hernández Rincón

Department of Family Medicine and Public Health, Universidad de La Sabana, Chía, Colombia

erwinhr@unisabana.edu.co

Puente del Comun University Campus, Km 7, North Highway of Chía 250001, Colombia

https://orcid.org/0000-0002-7189-5863

Nicolas Melo Sierra

Universidad de La Sabana, Chía, Colombia

https://orcid.org/0009-0009-4824-6572

Gabriela Alejandra Osorio Betancourt

Universidad de La Sabana, Chía, Colombia

https://orcid.org/0009-0005-6611-9244

Diana Marcela Díaz Quijano

Department of Epidemiology, Universidad de La Sabana, Chía, Colombia

https://orcid.org/0000-0001-8804-0274

Samuel David Barbosa Ardila

Universitat Oberta de Catalunya, Barcelona, Spain

https://orcid.org/0000-0002-8443-1670

Mariam Rolón Cadena

Pathology Department, Fundación Santa Fe de Bogotá, Bogotá, Colombia

https://orcid.org/0000-0003-0322-3042

Alejandro Rueda Rodríguez

Universidad de La Sabana, Chía, Colombia

https://orcid.org/0000-0001-8335-4370

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Historial

Citación Ramos Chaparro PA, Hernández Rincón E, Melo Sierra N, Osorio Betancourt GA, Díaz Quijano DM, Barbosa Ardila SDet al. Artificial intelligence for skin lesion classification and diagnosis in dermatology: A narrative review. Medwave 2025;25(10):e3120 doi: 10.5867/medwave.2025.10.3120

Envío 18/06/2025

Aceptación 26/08/2025

Publicación 20/11/2025

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Palabras claves

Dermatology, Artificial Intelligence, Diagnosis, Computer Aided Diagnosis

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