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Area of Science:

  • Medical Imaging
  • Artificial Intelligence
  • Radiography

Background:

  • Artificial intelligence (AI) adoption is increasing in medical imaging.
  • AI offers potential benefits for patient care, workflow optimization, and data analysis.
  • Radiographers' perspectives on AI integration are crucial for successful implementation.

Purpose of the Study:

  • To explore radiographers' knowledge, perceptions, and expectations regarding AI in medical imaging.
  • To evaluate an AI-based software for generating chest radiology reports.
  • To assess the accuracy of AI-generated reports compared to radiologist assessments.

Main Methods:

  • A cross-sectional survey was administered to 50 radiographers to assess AI knowledge and perceptions.
  • A retrospective analysis involved 40 chest radiographs analyzed by AI software (Siemens).
  • A radiologist evaluated the accuracy of AI-generated reports using a Likert scale.

Main Results:

  • 98% of radiographers believe they must adapt to AI technology, with 92% interested in AI training.
  • Radiographers' opinions on AI correlated significantly with their perceptions of AI education (p < 0.05).
  • Radiologists agreed with 53% of the AI-generated chest reports, indicating room for improvement.

Conclusions:

  • There is a clear demand for AI education and training among radiographers.
  • AI-powered tools demonstrate significant potential in advancing medical imaging analysis.
  • Further research and development are needed to enhance the accuracy and integration of AI in clinical practice.