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Artificial intelligence, machine learning, and deep learning in rhinology: a systematic review
PURPOSE: This PRISMA-compliant systematic review aims to analyze the existing applications of artificial intelligence (AI), machine learning, and deep learning for rhinological purposes and compare works in terms of data pool size, AI systems, input and outputs, and model reliability. METHODS: MEDLI...
Autores principales: | Bulfamante, Antonio Mario, Ferella, Francesco, Miller, Austin Michael, Rosso, Cecilia, Pipolo, Carlotta, Fuccillo, Emanuela, Felisati, Giovanni, Saibene, Alberto Maria |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9849161/ https://www.ncbi.nlm.nih.gov/pubmed/36260141 http://dx.doi.org/10.1007/s00405-022-07701-3 |
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