Table 2

- Artificial intelligence applications in radiology corresponding to gender, training level and familiar with big data.

Questions/answersn (%)P-value
  GenderTraining levelBig data
Should radiologists be educated on (choose at most 3):
 Clinical use of AI applications117 (76)
 Advantages and limitations of AI applications115 (74.7)
 Technical methods, such as machine/deep learning algorithm63 (40.9)
 How to get into the driver seat in using AI62 (40.3)
 How to survive the AI revolution29 (18.8)
 How to avoid the use of AI applications11 (7.1)
What are the advantages of using AI? (choose at most 2)
 AI can speed up processes in health care122 (79.2)0.2570.4680.748
 AI can help reduce medical errors73 (47.4)0.2980.7340.784
 AI has no emotional exhaustion nor physical limitation43 (27.9)1.000.1900.618
 AI can deliver vast amounts of clinically relevant high-quality data in real time27 (17.5)1.000.4400.582
 AI has no space-time constraint16 (10.4)0.8600.1181.00
What are you concerned about regarding the application of AI in medicine?
 It cannot be used to provide opinions in unpredicted situations due to inadequate information59 (38.3)
 It is not flexible enough to be applied to every patient53 (34.4)
 It is difficult to apply to controversial subjects21 (13.6)0.1930.1980.968
 The low ability to sympathize and consider the emotional well-being of the patient11 (7.1)
 It was developed by a less experienced medical clinician10 (6.5)
Are you involved in any research project based on AI-based application development
 Yes, testing5 (3.2)
 Yes, developing10 (6.5)0.4850.7740.027
 No, but planning to be involved44 (28.6)
 No95 (61.7)
Would you be willing to help in learning about ML and training a ML algorithm so that it can imitate some of the tasks you perform as a radiologist?
 Yes120 (77.9)0.0960.0490.026
 No34 (22.1)
  • AI: artificial intelligence, ML: machine learning, Fisher’s exact test