E-ISSN 2534-9821
 

Original Research 


Radiologist Knowledge of Artificial Intelligence on Diagnostic radiology: A survey-based study

Viswanathan Murugaiah, Dharan Venkatesh K.A, Krishna Kumar M, Senthilnathan V.

Abstract
Background & Aims: Artificial intelligence (AI) has lately made significant advancements in perception, enabling machines to represent complicated facts, many clinical procedures were automated using AI, transforming radiology from a perceptually subjective trade to a mathematically calculable area. The radiologists participating in the residency program don't know how to employ artificial intelligence in clinical settings or how it fits into diagnostic radiology. So, this study is an attempt to determine the knowledge of AI among radiologists. Material and Methods: A online survey was done using google forms circulated through Whatsapp groups of radiologists for the assessment of knowledge regarding AI among them. The questionnaire consists of ten questions related to AI usefulness and knowledge of AI in diagnostic radiology. Data was transformed into an excel sheet and analyzed using descriptive and inferential statistics by SPSS software Result: The knowledge of AI was better among respondents and senior consultant radiologists had good knowledge regarding artificial intelligence and junior residents were lacking in some areas. Conclusions: The level of AI expertise among radiology staff members seriously influences their readiness to learn, apply, and modify this technology in clinical settings.

Key words: Artificial intelligence, diagnostic radiology, knowledge, radiologist


 
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How to Cite this Article
Pubmed Style

Murugaiah V, K.A DV, M KK, V S. Radiologist Knowledge of Artificial Intelligence on Diagnostic radiology: A survey-based study. Int J Med Rev Case Rep. 2022; 6(16): 70-74. doi:10.5455/IJMRCR.172-1667143395


Web Style

Murugaiah V, K.A DV, M KK, V S. Radiologist Knowledge of Artificial Intelligence on Diagnostic radiology: A survey-based study. https://www.mdpub.net/?mno=125783 [Access: January 14, 2023]. doi:10.5455/IJMRCR.172-1667143395


AMA (American Medical Association) Style

Murugaiah V, K.A DV, M KK, V S. Radiologist Knowledge of Artificial Intelligence on Diagnostic radiology: A survey-based study. Int J Med Rev Case Rep. 2022; 6(16): 70-74. doi:10.5455/IJMRCR.172-1667143395



Vancouver/ICMJE Style

Murugaiah V, K.A DV, M KK, V S. Radiologist Knowledge of Artificial Intelligence on Diagnostic radiology: A survey-based study. Int J Med Rev Case Rep. (2022), [cited January 14, 2023]; 6(16): 70-74. doi:10.5455/IJMRCR.172-1667143395



Harvard Style

Murugaiah, V., K.A, . D. V., M, . K. K. & V, . S. (2022) Radiologist Knowledge of Artificial Intelligence on Diagnostic radiology: A survey-based study. Int J Med Rev Case Rep, 6 (16), 70-74. doi:10.5455/IJMRCR.172-1667143395



Turabian Style

Murugaiah, Viswanathan, Dharan Venkatesh K.A, Krishna Kumar M, and Senthilnathan V. 2022. Radiologist Knowledge of Artificial Intelligence on Diagnostic radiology: A survey-based study. International Journal of Medical Reviews and Case Reports, 6 (16), 70-74. doi:10.5455/IJMRCR.172-1667143395



Chicago Style

Murugaiah, Viswanathan, Dharan Venkatesh K.A, Krishna Kumar M, and Senthilnathan V. "Radiologist Knowledge of Artificial Intelligence on Diagnostic radiology: A survey-based study." International Journal of Medical Reviews and Case Reports 6 (2022), 70-74. doi:10.5455/IJMRCR.172-1667143395



MLA (The Modern Language Association) Style

Murugaiah, Viswanathan, Dharan Venkatesh K.A, Krishna Kumar M, and Senthilnathan V. "Radiologist Knowledge of Artificial Intelligence on Diagnostic radiology: A survey-based study." International Journal of Medical Reviews and Case Reports 6.16 (2022), 70-74. Print. doi:10.5455/IJMRCR.172-1667143395



APA (American Psychological Association) Style

Murugaiah, V., K.A, . D. V., M, . K. K. & V, . S. (2022) Radiologist Knowledge of Artificial Intelligence on Diagnostic radiology: A survey-based study. International Journal of Medical Reviews and Case Reports, 6 (16), 70-74. doi:10.5455/IJMRCR.172-1667143395