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  2. Vol 54, No 1 (2024)
  3. Malkic

ANALYSIS OF CHALLENGES AND PERSPECTIVES IN THE ACCEPTANCE OF ARTIFICIAL INTELLIGENCE IN RADIOLOGY BY HEALTHCARE WORKERS

Benjamin Malkic, Nihad Mesanovic

Abstract


Aim: The research aims to explore healthcare workers' attitudes towards and acceptance of artificial intelligence in radiology, focusing on its potential to enhance diagnostic accuracy, reduce waiting times, increase service efficiency, and improve patient care. It seeks to assess their willingness to adopt artificial intelligence, along with their concerns, expectations, and educational needs to effectively utilize this technology in radiological practice.Methods: A prospective study surveyed 50 healthcare workers, including radiologists, technicians, nurses, and others using various radiological techniques for diagnosing diseases. Using a quantitative approach, numerical data from distributed surveys assessed their attitudes and knowledge regarding artificial intelligence  in radiology. Conducted at Public Health Institution "Zdravstveni centar Brcko" in Bosnia and Herzegovina's Brcko District over 60 days, the research adhered to ethical principles and received approval from the center's Ethics Committee.Results: The majority of respondents recognize the potential of artificial intelligence to improve the efficiency of radiological services and treatment processes, but at the same time express the need for additional education and training in order to optimally use this technology. Despite the positive perception, part of the respondents are still not sure about the use of artificial intelligence, which emphasizes the importance of continuous information and education of healthcare workers.Conclusion: Ultimately, the research results indicate the importance of further steps in the implementation of artificial intelligence in radiology in order to improve the quality of health care and optimize treatment processes.Keywords: Artificial intelligence, radiological diagnostics, challenges, perspectives, quality of health care.


Keywords


Artificial intelligence, radiological diagnostics, challenges, perspectives, quality of health care.

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Full Text: PDF

DOI: 10.5457/ams.v54i1.809

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