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Artificial Intelligence in Rhinology.
Ayoub, Noel F; Glicksman, Jordan T.
Afiliação
  • Ayoub NF; Department of Otolaryngology-Head & Neck Surgery, Mass Eye and Ear/Harvard Medical School, Boston, MA, USA. Electronic address: fayoub@meei.harvard.edu.
  • Glicksman JT; Department of Otolaryngology-Head & Neck Surgery, Mass Eye and Ear/Harvard Medical School, Boston, MA, USA.
Otolaryngol Clin North Am ; 57(5): 831-842, 2024 Oct.
Article em En | MEDLINE | ID: mdl-38821734
ABSTRACT
Rhinology, allergy, and skull base surgery are fields primed for the integration and implementation of artificial intelligence (AI). The heterogeneity of the disease processes within these fields highlights the opportunity for AI to augment clinical care and promote personalized medicine. Numerous research studies have been published demonstrating the development and clinical potential of AI models within the field. Most describe in silico evaluation models without direct clinical implementation. The major themes of existing studies include diagnostic or clinical decisions support, clustering patients into specific phenotypes or endotypes, predicting post-treatment outcomes, and surgical planning.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Otolaringologia / Inteligência Artificial Limite: Humans Idioma: En Revista: Otolaryngol Clin North Am / Otolaryngol. clin / Otolaryngologic clinics of North America Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Otolaringologia / Inteligência Artificial Limite: Humans Idioma: En Revista: Otolaryngol Clin North Am / Otolaryngol. clin / Otolaryngologic clinics of North America Ano de publicação: 2024 Tipo de documento: Article
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