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The Future of Artificial Intelligence Using Images and Clinical Assessment for Difficult Airway Management.
De Rosa, Silvia; Bignami, Elena; Bellini, Valentina; Battaglini, Denise.
Afiliação
  • De Rosa S; From the Centre for Medical Sciences - CISMed, University of Trento, Trento, Italy.
  • Bignami E; Anesthesia and Intensive Care, Santa Chiara Regional Hospital, APSS Trento, Trento, Italy.
  • Bellini V; Anesthesiology, Critical Care and Pain Medicine Division, Department of Medicine and Surgery, University of Parma, Parma, Italy.
  • Battaglini D; Anesthesiology, Critical Care and Pain Medicine Division, Department of Medicine and Surgery, University of Parma, Parma, Italy.
Anesth Analg ; 2024 Apr 01.
Article em En | MEDLINE | ID: mdl-38557728
ABSTRACT
Artificial intelligence (AI) algorithms, particularly deep learning, are automatic and sophisticated methods that recognize complex patterns in imaging data providing high qualitative assessments. Several machine-learning and deep-learning models using imaging techniques have been recently developed and validated to predict difficult airways. Despite advances in AI modeling. In this review article, we describe the advantages of using AI models. We explore how these methods could impact clinical practice. Finally, we discuss predictive modeling for difficult laryngoscopy using machine-learning and the future approach with intelligent intubation devices.

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Anesth Analg Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Itália

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Anesth Analg Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Itália