Title of article :
Evaluation of radiologist’s knowledge about the Artificial Intelligence in diagnostic radiology: a survey-based study
Author/Authors :
Tajaldeen, Abdulrahman Radiological Science Department - College of Applied Medical Science - Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia , Alghamdi, Salem Department of Medical Imaging and Radiation Sciences - Collage of Applied Medical Sciences - University of Jeddah, Jeddah, Saudi Arabia
Pages :
6
From page :
1
To page :
6
Abstract :
Background Advanced developments in diagnostic radiology have provided a rapid increase in the number of radiological investigations worldwide. Recently, Artificial Intelligence (AI) has been applied in diagnostic radiology. The purpose of developing such applications is to clinically validate and make them feasible for the current practice of diagnostic radiology, in which there is less time for diagnosis. Purpose To assess radiologists’ knowledge about AI’s role and establish a baseline to help in providing educational activities on AI in diagnostic radiology in Saudi Arabia. Material and Methods An online questionnaire was designed using QuestionPro software. The study was conducted in large hospitals located in different regions in Saudi Arabia. A total of 93 participants completed the questionnaire, of which 32 (34%) were trainee radiologists from year 1 to year 4 (R1–R4) of the residency programme, 33 (36%) were radiologists and fellows, and 28 (30%) were consultants. Results The responses to the question related to the use of AI on a daily basis illustrated that 76 (82%) of the participants were not using any AI software at all during daily interpretation of diagnostic images. Only 17 (18%) reported that they used AI software for diagnostic radiology. Conclusion There is a significant lack of knowledge about AI in our residency programme and radiology departments at hospitals. Due to the rapid development of AI and its application in diagnostic radiology, there is an urgent need to enhance awareness about its role in different diagnostic fields.
Keywords :
Diagnostic radiology , artificial intelligence , machine learning
Journal title :
Acta Radiologica Open
Serial Year :
2020
Full Text URL :
Record number :
2620544
Link To Document :
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