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The Algorithmic Lung Detective: Artificial Intelligence in the Diagnosis of Pulmonary Embolism.
Allena, Nishant; Khanal, Sneha.
Afiliación
  • Allena N; Pulmonary Medicine, BronxCare Health System, Bronx, USA.
  • Khanal S; Internal Medicine, BronxCare Health System, Bronx, USA.
Cureus ; 15(12): e51006, 2023 Dec.
Article en En | MEDLINE | ID: mdl-38259362
ABSTRACT
Pulmonary embolism (PE) poses a significant threat as the third leading cause of cardiovascular death, prompting the widespread use of CT pulmonary angiogram for rapid detection. Despite its prevalence, diagnostic accuracy remains variable among radiologists. The emergence of artificial intelligence (AI), notably through convolutional neural networks and deep learning reconstruction, offers a promising avenue to enhance PE detection. AI demonstrates superior sensitivity and negative predictive values, reducing the risk of missed diagnoses. Implementation of AI-based worklist prioritization substantially shortens detection and notification times, streamlining radiological workflows. However, it is crucial to underscore that AI acts as a complement, not a replacement, for radiologists, synergizing with human expertise. As AI integration progresses, it holds the potential to significantly improve diagnostic accuracy and efficiency in pulmonary embolism detection while maintaining the essential role of human judgment in medical decision-making.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Diagnostic_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: Cureus Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Diagnostic_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: Cureus Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos