ID Consecutivo : 1915

Titulo

serie

Editorial

 

ISBN

Año de publicación Edición Primera Segunda Tercera Cuarta Quita Sexta Septima Octava Novena Decima Selecione una

Paginas Existencias 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

Resumen
In the era of personalized medicine, the emphasis of health care is shifting from populations to individuals. Artificial intelligence (AI) is capable of learning without explicit instruction and has emerging applications in medicine, particularly radiology. Whereas much attention has focused on teaching radiology trainees about AI, here our goal is to instead focus on how AI might be developed to better teach radiology trainees. While the idea of using AI to improve education is not new, the application of AI to medical and radiological education remains very limited. Based on the current educational foundation, we highlight an AI-integrated framework to augment radiology education and provide use case examples informed by our own institution's practice. The coming age of "AI-augmented radiology" may enable not only "precision medicine" but also what we describe as "precision medical education," where instruction is tailored to individual trainees based on their learning styles and needs.

 

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Idioma Español Inglés Portugués Francés Alemán

 

Tipo de Acceso

Restringido(ASCOFAME)

Libre

Registrado

Palabras clave

Coleccion ASCOFAME: Investigacion Desarrollo Profesional continuo Gestion curricular Calidad y acreditacion Evaluacion Investigacion Desarrollo Profesional

Disponibilidad:	Digital	Físico	Físico y Digital	Link Externo

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Publico	Pregrado	Posgrado	Decanatura
Objetivo:	Docentes	Médicos	Investigadores
	Clínicos	Educadores Médicos	Otros profesionales de la salud
	Evaluadores

 

Signatura topografica:

ID Consecutivo : 1915

Titulo

Editorial

 

Año de publicación Edición Primera Segunda Tercera Cuarta Quita Sexta Septima Octava Novena Decima Selecione una

Paginas Existencias 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

Resumen
In the era of personalized medicine, the emphasis of health care is shifting from populations to individuals. Artificial intelligence (AI) is capable of learning without explicit instruction and has emerging applications in medicine, particularly radiology. Whereas much attention has focused on teaching radiology trainees about AI, here our goal is to instead focus on how AI might be developed to better teach radiology trainees. While the idea of using AI to improve education is not new, the application of AI to medical and radiological education remains very limited. Based on the current educational foundation, we highlight an AI-integrated framework to augment radiology education and provide use case examples informed by our own institution's practice. The coming age of "AI-augmented radiology" may enable not only "precision medicine" but also what we describe as "precision medical education," where instruction is tailored to individual trainees based on their learning styles and needs.

 

Adjunte la portada del libro Si no tiene una imagen, descargue aqui la imagen de Ascofame

Idioma Español Inglés Portugués Francés Alemán

 

Tipo de Acceso

Restringido(ASCOFAME)

Libre

Registrado

Palabras clave

Coleccion ASCOFAME: Investigacion Desarrollo Profesional continuo Gestion curricular Calidad y acreditacion Evaluacion Investigacion Desarrollo Profesional

Disponibilidad:	Digital	Físico	Físico y Digital	Link Externo

Cargue el Documento

Ingrese el Link: ejemplo: http://www.google.com.co

 

Publico	Pregrado	Posgrado	Decanatura
Objetivo:	Docentes	Médicos	Investigadores
	Clínicos	Educadores Médicos	Otros profesionales de la salud
	Evaluadores

 

Signatura topografica:

ID Consecutivo : 1915

Titulo

Tipo : Ley Decreto Norma Resolucion Circular Directiva

 

Año de publicación

Resumen
In the era of personalized medicine, the emphasis of health care is shifting from populations to individuals. Artificial intelligence (AI) is capable of learning without explicit instruction and has emerging applications in medicine, particularly radiology. Whereas much attention has focused on teaching radiology trainees about AI, here our goal is to instead focus on how AI might be developed to better teach radiology trainees. While the idea of using AI to improve education is not new, the application of AI to medical and radiological education remains very limited. Based on the current educational foundation, we highlight an AI-integrated framework to augment radiology education and provide use case examples informed by our own institution's practice. The coming age of "AI-augmented radiology" may enable not only "precision medicine" but also what we describe as "precision medical education," where instruction is tailored to individual trainees based on their learning styles and needs.

 

Adjunte la portada del libro Si no tiene una imagen, descargue aqui la imagen de Ascofame

Idioma Español Inglés Portugués Francés Alemán

 

Tipo de Acceso

Restringido(ASCOFAME)

Libre

Registrado

Palabras clave

Coleccion ASCOFAME: Investigacion Desarrollo Profesional continuo Gestion curricular Calidad y acreditacion Evaluacion Investigacion Desarrollo Profesional

Disponibilidad:	Digital	Físico	Físico y Digital	Link Externo

Cargue el Documento

Ingrese el Link: ejemplo: http://www.google.com.co

 

Publico	Pregrado	Posgrado	Decanatura
Objetivo:	Docentes	Médicos	Investigadores
	Clínicos	Educadores Médicos	Otros profesionales de la salud
	Evaluadores

 

ID Consecutivo : 1915

Titulo

Autor como conferencia

Paginas

 

Año de publicación

Resumen
In the era of personalized medicine, the emphasis of health care is shifting from populations to individuals. Artificial intelligence (AI) is capable of learning without explicit instruction and has emerging applications in medicine, particularly radiology. Whereas much attention has focused on teaching radiology trainees about AI, here our goal is to instead focus on how AI might be developed to better teach radiology trainees. While the idea of using AI to improve education is not new, the application of AI to medical and radiological education remains very limited. Based on the current educational foundation, we highlight an AI-integrated framework to augment radiology education and provide use case examples informed by our own institution's practice. The coming age of "AI-augmented radiology" may enable not only "precision medicine" but also what we describe as "precision medical education," where instruction is tailored to individual trainees based on their learning styles and needs.

 

Adjunte la portada del libro Si no tiene una imagen, descargue aqui la imagen de Ascofame

Idioma Español Inglés Portugués Francés Alemán

 

Tipo de Acceso

Restringido(ASCOFAME)

Libre

Registrado

Palabras clave

Coleccion ASCOFAME: Investigacion Desarrollo Profesional continuo Gestion curricular Calidad y acreditacion Evaluacion Investigacion Desarrollo Profesional

Disponibilidad:	Digital	Físico	Físico y Digital	Link Externo

Cargue el Documento

Ingrese el Link: ejemplo: http://www.google.com.co

 

Publico	Pregrado	Posgrado	Decanatura
Objetivo:	Docentes	Médicos	Investigadores
	Clínicos	Educadores Médicos	Otros profesionales de la salud
	Evaluadores

 

ID Consecutivo : 1915

Titulo

 

Año de publicación

Producción de publicación

Volumen

ISBN

Frecuencia

Resumen
In the era of personalized medicine, the emphasis of health care is shifting from populations to individuals. Artificial intelligence (AI) is capable of learning without explicit instruction and has emerging applications in medicine, particularly radiology. Whereas much attention has focused on teaching radiology trainees about AI, here our goal is to instead focus on how AI might be developed to better teach radiology trainees. While the idea of using AI to improve education is not new, the application of AI to medical and radiological education remains very limited. Based on the current educational foundation, we highlight an AI-integrated framework to augment radiology education and provide use case examples informed by our own institution's practice. The coming age of "AI-augmented radiology" may enable not only "precision medicine" but also what we describe as "precision medical education," where instruction is tailored to individual trainees based on their learning styles and needs.

 

Adjunte la portada del libro Si no tiene una imagen, descargue aqui la imagen de Ascofame

Idioma Español Inglés Portugués Francés Alemán

 

Tipo de Acceso

Restringido(ASCOFAME)

Libre

Registrado

Palabras clave

Coleccion ASCOFAME: Investigacion Desarrollo Profesional continuo Gestion curricular Calidad y acreditacion Evaluacion Investigacion Desarrollo Profesional

Disponibilidad:	Digital	Físico	Físico y Digital	Link Externo

Cargue el Documento

Ingrese el Link: ejemplo: http://www.google.com.co

 

Publico	Pregrado	Posgrado	Decanatura
Objetivo:	Docentes	Médicos	Investigadores
	Clínicos	Educadores Médicos	Otros profesionales de la salud
	Evaluadores

 

ID Consecutivo : 1915

Titulo videos

Año de publicación

Resumen
In the era of personalized medicine, the emphasis of health care is shifting from populations to individuals. Artificial intelligence (AI) is capable of learning without explicit instruction and has emerging applications in medicine, particularly radiology. Whereas much attention has focused on teaching radiology trainees about AI, here our goal is to instead focus on how AI might be developed to better teach radiology trainees. While the idea of using AI to improve education is not new, the application of AI to medical and radiological education remains very limited. Based on the current educational foundation, we highlight an AI-integrated framework to augment radiology education and provide use case examples informed by our own institution's practice. The coming age of "AI-augmented radiology" may enable not only "precision medicine" but also what we describe as "precision medical education," where instruction is tailored to individual trainees based on their learning styles and needs.

 

Adjunte la Imagen del Video

 

Idioma Español Inglés Portugués Francés Alemán

 

Tipo de Acceso

Restringido(ASCOFAME)

Libre

Registrado

Palabras clave

Coleccion ASCOFAME: Investigacion Desarrollo Profesional continuo Gestion curricular Calidad y acreditacion Evaluacion Investigacion Desarrollo Profesional

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6849670/pdf/bjr.20190389.pdf

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Publico	Pregrado	Posgrado	Decanatura
Objetivo:	Docentes	Médicos	Investigadores
	Clínicos	Educadores Médicos	Otros profesionales de la salud
	Evaluadores

 

ID Consecutivo : 1915

Titulo

Titulo Revista

ISSN

Año de publicación Suplemento

Numero: Volumen

Pagina Inicial Pagina Final

Resumen
In the era of personalized medicine, the emphasis of health care is shifting from populations to individuals. Artificial intelligence (AI) is capable of learning without explicit instruction and has emerging applications in medicine, particularly radiology. Whereas much attention has focused on teaching radiology trainees about AI, here our goal is to instead focus on how AI might be developed to better teach radiology trainees. While the idea of using AI to improve education is not new, the application of AI to medical and radiological education remains very limited. Based on the current educational foundation, we highlight an AI-integrated framework to augment radiology education and provide use case examples informed by our own institution's practice. The coming age of "AI-augmented radiology" may enable not only "precision medicine" but also what we describe as "precision medical education," where instruction is tailored to individual trainees based on their learning styles and needs.

 

Base de datos bibliográfica Base de datos bibliográfica Seleccione una Access Medicine Biblioteca VirtualenSalud(BVS) Cochrane Central Dialnet Lilacs-Literatura Latinoamericana en Ciencias de la Salud Medline-PubMed Redalyc ScienceDirect SciELO-Scientific Electronic Library Online WHOLIS Otra

Imagen de portada

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Idioma Español Inglés Portugués Francés Alemán

 

Tipo de Acceso

Restringido(ASCOFAME)

Libre

Registrado

Palabras clave

Coleccion ASCOFAME: Investigacion Desarrollo Profesional continuo Gestion curricular Calidad y acreditacion Evaluacion Investigacion Desarrollo Profesional

Disponibilidad:	Digital	Físico	Físico y Digital	Link Externo

Cargue el Documento

Ingrese el Link: ejemplo: http://www.google.com.co

 

Publico	Pregrado	Posgrado	Decanatura
Objetivo:	Docentes	Médicos	Investigadores
	Clínicos	Educadores Médicos	Otros profesionales de la salud
	Evaluadores