CADTH | Evidence Driven
CADTH | Evidence Driven

Artificial Intelligence for Classification of Lung Nodules: Clinical Utility, Diagnostic Accuracy, Cost-Effectiveness, and Guidelines

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Project Status:
Completed
Project Line:
Reference List
Project Sub Line:
Summary of Abstracts
Project Number:
RB1411-000

Question

  1. What is the clinical utility of artificial intelligence for nodule classification in screening, incidental identification, or known or suspected malignancies for lung cancer?
  2. What is the diagnostic accuracy of artificial intelligence for nodule classification in screening, incidental identification, or known or suspected malignancies for lung cancer?
  3. What is the cost-effectiveness of artificial intelligence for nodule classification in screening, incidental identification, or known or suspected malignancies for lung cancer?
  4. What are the evidence-based guidelines regarding artificial intelligence for nodule classification in screening, incidental identification, or known or suspected malignancies for lung cancer?

Key Message

Two randomized controlled trials and twelve non-randomized studies were identified regarding the clinical utility and diagnostic accuracy of artificial intelligence for nodule classification in screening, incidental identification, or known or suspected malignancies for lung cancer.

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Artificial Intelligence for Classification of Lung Nodules: Clinical Utility, Diagnostic Accuracy, Cost-Effectiveness, and Guidelines Rapid Response November 14, 2019 View PDF

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Last Updated : November 14, 2019