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Attitudes Toward Artificial Intelligence Among Radiologists, IT Specialists, and Industry
- Source :
- Academic Radiology.
- Publication Year :
- 2020
- Publisher :
- Elsevier BV, 2020.
-
Abstract
- Objectives We investigated the attitudes of radiologists, information technology (IT) specialists, and industry representatives on artificial intelligence (AI) and its future impact on radiological work. Materials and Methods During a national meeting for AI, eHealth, and IT infrastructure in 2019, we conducted a survey to obtain participants’ attitudes. A total of 123 participants completed 28 items exploring AI usage in medicine. The Kruskal-Wallis test was used to identify differences between radiologists, IT specialists, and industry representatives. Results The strongest agreement between all respondents occurred with the following: plausibility checks are important to understand the decisions of the AI (93% agreement), validation of AI algorithms is mandatory (91%), and medicine becomes more efficient in the age of AI (86%). In contrast, only 25% of the respondents had confidence in the AI results, and only 17% believed that medicine will become more human through the use of AI. The answers were significantly different between the three professions for four items: relevance for protocol selection in cross-sectional imaging (p = 0.034), medical societies should be involved in validation (p = 0.028), patients should be informed about the use of AI (p = 0.047), and AI should be part of medical education (p = 0.026). Conclusion Currently, a discrepancy exists between high expectations for the future role of AI and low confidence in the results. This attitude was similar across all three groups. The demand for plausibility checks and the need to prove the usefulness in randomized controlled studies indicate what is needed in future research.
- Subjects :
- Protocol (science)
business.industry
Low Confidence
Information technology
Controlled studies
030218 nuclear medicine & medical imaging
Test (assessment)
03 medical and health sciences
0302 clinical medicine
Artificial Intelligence
030220 oncology & carcinogenesis
Radiologists
Information technology management
eHealth
Humans
Radiology, Nuclear Medicine and imaging
Relevance (information retrieval)
Artificial intelligence
Information Technology
Radiology
business
Psychology
Specialization
Subjects
Details
- ISSN :
- 10766332
- Database :
- OpenAIRE
- Journal :
- Academic Radiology
- Accession number :
- edsair.doi.dedup.....2e62be469c3e7bb0d7b6f4540f204e4a
- Full Text :
- https://doi.org/10.1016/j.acra.2020.04.011