Physician Confidence in Artificial Intelligence: An Online Mobile Survey
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Abstract
BACKGROUND: It is expected that artificial intelligence (AI) will be used extensively in the medical field in the future. OBJECTIVE: The purpose of this study is to investigate the awareness of AI among Korean doctors and to assess physicians' attitudes toward the medical application of AI. METHODS: We conducted an online survey composed of 11 closed-ended questions using Google Forms. The survey consisted of questions regarding the recognition of and attitudes toward AI, the development direction of AI in medicine, and the possible risks of using AI in the medical field. RESULTS: A total of 669 participants completed the survey. Only 40 (5.9%) answered that they had good familiarity with AI. However, most participants considered AI useful in the medical field (558/669, 83.4% agreement). The advantage of using AI was seen as the ability to analyze vast amounts of high-quality, clinically relevant data in real time. Respondents agreed that the area of medicine in which AI would be most useful is disease diagnosis (558/669, 83.4% agreement). One possible problem cited by the participants was that AI would not be able to assist in unexpected situations owing to inadequate information (196/669, 29.3%). Less than half of the participants(294/669, 43.9%) agreed that AI is diagnostically superior to human doctors. Only 237 (35.4%) answered that they agreed that AI could replace them in their jobs. CONCLUSIONS: This study suggests that Korean doctors and medical students have favorable attitudes toward AI in the medical field. The majority of physicians surveyed believed that AI will not replace their roles in the future.
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This positive outlook towards AI is consistent with other studies showing clinicians' openness to AI-based CDSS if they enhance clinical practice and improve patient outcomes.
“This positive outlook towards AI is consistent with other studies showing clinicians’ openness to AI-based CDSS if they enhance clinical practice and improve patient outcomes [37].”
From Expectations of Intensive Care Physicians Regarding an AI-Based Decision Support System for Weaning From Continuous Renal Replacement Therapy: Predevelopment Survey Study (2025) · cites this paper as [37]
The Discussion (page unavailable) reports that physicians and medical students regarded AI as useful, particularly for diagnosis and treatment planning. It does not establish that clinicians were open specifically to AI-based CDSS on the condition that they improve clinical practice or patient outcomes. (LLM, conf=0.86)
Experimental — accuracy not yet measuredMedical students are often not familiar with AI and may be worried about the potential for job loss.
“Previous studies have shown that medical students are often not familiar with AI and may be worried about the potential for job loss [13–15].”
From AI in medical education: medical student perception, curriculum recommendations and design suggestions (2023) · cites this paper as [15]
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- Authors
- Oh, S., Kim, J. H., Choi, S.-W., Lee, H. J., Hong, J., & Kwon, S. H.
- Affiliations
- Soonchunhyang University Hospital Seoul (KR)
- Soonchunhyang University (KR)
- New York Medical College (US)
- Corresponding author
- Kwon, Soon Hyo
- Venue
- Journal of Medical Internet Research
- Publisher
- JMIR Publications Inc.
- Published
- 2019-03-25
- Volume
- 21
- Issue
- 3
- Pages
- e12422
- ISSN
- 1438-8871 (ISSN-L)
- PMC
- PMC6452288
- OpenAlex
- W2910165844
- Cited by
- 387
- References
- 43
- Citations by year
- 2026: 63 · 2025: 71 · 2024: 86 · 2023: 64 · 2022: 52 · 2021: 26 · 2020: 20 · 2019: 4
- FWCI
- 8.11
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- Journal of Medical Internet Research (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Funders
- Soonchunhyang University
- Topics
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Physical Sciences › Computer Science › Artificial Intelligence › Artificial Intelligence Applications
- Social Sciences › Safety Research › Ethics and Social Impacts of AI
- Keywords
- artificial intelligence in healthcare, physician attitudes, AI awareness, AI adoption in healthcare, disease diagnosis, Korean physicians, medical students
- MeSH terms
- Artificial Intelligence, Female, Humans, Male, Physicians, Surveys and Questionnaires, Mobile Applications
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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