Artificial intelligence in medical education: Latin American context

Autores/as

DOI:

https://doi.org/10.47464/MetroCiencia/vol31/2/2023/21-34

Palabras clave:

artificial intelligence, medical education, Latin American, medical skills, support tool, updating, effectiveness, challenges

Resumen

Introduction: Artificial Intelligence (AI) is an algorithm and statistic technology used in many human competences. In health, it works as a support tool centered in managing the use of data for clinical performance and learning medical skills, improving the health response from professionals. Methods: This paper collects and analyzes previous research, in electronic databases, related to the use of artificial intelligence in medical education within the Latin American context. No exclusion criteria were applied. Results: Artificial intelligence (AI) is considered an effective support tool for the development of multidisciplinary learning and teaching strategies focused on improving medical care through updating the process in medical training. For its correct use, it is important to define a support approach and its competent training to facilitate its effective implementation, reducing the gap between ethical and legal debates. The Latin American region, due to its political and sociocultural context, presents different challenges that must be faced to integrate these technologies into health education, occupation, and acceptation. Conclusion: In medical education AI is used as a tool which is a support for students and doctors, but it won't be a replacement. In Latin American it is the key for improving the education. AI must be operated or regulated by humans because it doesn't consider civil liberties and it hasn't conscience.

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Biografía del autor/a

Daniel Aguilar Bucheli, Universidad Internacional SEK

Universidad Internacional SEK, Quito, Ecuador

Marlo Alexander Borja Espinoza, Universidad Internacional SEK

Universidad Internacional SEK, Quito, Ecuador

Emilia Fabiana Cadena Vargas, Universidad Internacional SEK

Universidad Internacional SEK, Quito, Ecuador

Stefano Adrián Endara Regalado, Universidad de las Américas

Universidad de las Américas, Quito, Ecuador

Daniela Bernarda Endara Sánchez, Universidad Internacional SEK

Universidad Internacional SEK, Quito, Ecuador

Danna Leonela Feijóo Jiménez, Universidad Internacional SEK

Universidad Internacional SEK, Quito, Ecuador

Doménica Alejandra Jácome Castillo, Universidad de las Américas

Universidad de las Américas, Quito, Ecuador

Danna Micaela Jiménez Álvarez, Universidad Internacional SEK

Universidad Internacional SEK, Quito, Ecuador

Ariel Sebastián Pazmiño Troncoso, Universidad Internacional SEK

Universidad Internacional SEK, Quito, Ecuador

David Sebastián Valladares Izurieta, Universidad Internacional SEK

Universidad Internacional SEK, Quito, Ecuador

Sandra Malena Alcocer Veintimilla, Universidad Internacional SEK

Universidad Internacional SEK, Quito, Ecuador

María Belén Herrera Flores, Universidad Internacional SEK

Universidad Internacional SEK, Quito, Ecuador

Doménica Salomé Pérez Rueda, Universidad Internacional SEK

Universidad Internacional SEK, Quito, Ecuador

Víctor Andrés Pillajo Gangotena, Universidad Internacional SEK

Universidad Internacional SEK, Quito, Ecuador

Nicolás Josué Sánchez Sánchez, Universidad Internacional SEK

Universidad Internacional SEK, Quito, Ecuador

Raffaella Bedoya Aliatis, Universidad Internacional SEK

Universidad Internacional SEK, Quito, Ecuador

Shannon Valeria Guaycha Apolo, Universidad Internacional SEK

Universidad Internacional SEK, Quito, Ecuador

Citas

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Publicado

2023-06-30

Cómo citar

Aguilar Bucheli, D., Borja Espinoza, M. A., Cadena Vargas, E. F., Endara Regalado, S. A., Endara Sánchez, D. B., Feijóo Jiménez, D. L., Jácome Castillo, D. A., Jiménez Álvarez, D. M., Pazmiño Troncoso, A. S., Valladares Izurieta, D. S., Alcocer Veintimilla, S. M., Herrera Flores, . M. B., Pérez Rueda, D. S., Pillajo Gangotena, V. A., Sánchez Sánchez, N. J., Bedoya Aliatis, R., & Guaycha Apolo, S. V. (2023). Artificial intelligence in medical education: Latin American context. Metro Ciencia, 31(2), 21–34. https://doi.org/10.47464/MetroCiencia/vol31/2/2023/21-34

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