Bienvenido
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Titulo Artículo : | Artificial intelligence for precision education in radiology | |||
| Titulo Revista: | The British journal of radiology |
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ISBN | 1748-880X | ||||
| Autores | Andreas M. Rauschecker Jeffrey D. Rudie Po-Hao Chen Tessa S. Cook R. Nick Bryan Suyash Mohan Michael Tran Duong |
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| Año de publicacion | 2019 | ||||
Suplemento |
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| Numero | Volumen | 92 | |||
| Pagina Inicial | 1 | Pagina Final | 11 | ||
| Idioma: | Inglés | Base de datos bibliográfica: | Medline-PubMed |
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| 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. | ||||
| Palabras Claves : | Educación médica Artificial Intelligence Radiology |
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Tipo de acceso: |
libre | Disponibilidad | Link Externo |  |
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| Publico Objetivo: | Docentes , Medicos , Otros profesionales de la salud , | ||||