ArticleRadiologia brasileira
Impact of artificial intelligence on the choice of radiology as a specialty by medical students from the city of São Paulo.
Article in Radiologia brasileira. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
12 citing papers in PubMed.
- Artificial intelligence in dentistry: awareness among dentists and computer scientists.Oral radiology · 2025Article
- Medical students and house officers' perception, attitude and potential barriers towards artificial intelligence in Egypt, cross sectional survey.BMC medical education · 2024Article
- Knowledge, attitude, and perception of Arab medical students towards artificial intelligence in medicine and radiology: A multi-national cross-sectional study.European radiology · 2024Article
- Exploring clinical specialists' perspectives on the future role of AI: evaluating replacement perceptions, benefits, and drawbacks.BMC health services research · 2024Article
- Healthcare students' knowledge, attitudes, and perspectives toward artificial intelligence in the southern Vietnam.Heliyon · 2023Article
- Article
- Attitudes, knowledge, and skills towards artificial intelligence among healthcare students: A systematic review.Health science reports · 2023Article
- Impact of the Rise of Artificial Intelligence in Radiology: What Do Students Think?International journal of environmental research and public health · 2023Article
- Acceptance of clinical artificial intelligence among physicians and medical students: A systematic review with cross-sectional survey.Frontiers in medicine · 2022Article
- Article
- Artificial Intelligence in Medicine: A Multinational Multi-Center Survey on the Medical and Dental Students' Perception.Frontiers in public health · 2021Article
- Artificial intelligence in radiology: does it impact medical students preference for radiology as their future career?BJR open · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo evaluate the impact of artificial intelligence (AI) on undergraduate medical students' choice of radiology as a specialty. MATERIALS AND
methodsIn February 2019, an anonymous online survey was sent to medical students. The research contemplated questions on how much students think they know about AI technologies, how much AI discourages them from choosing radiology as a specialty, and whether they believe there is a threat to the radiology job market.
resultsA total of 101 students, most of them doing their internship, answered the questionnaire. More than half of them (52.5%) said they believe AI poses a threat to the radiology job market, but 64.3% claimed not to have proper knowledge about these new technologies, and 31.7% said they would like more information on the technologies' operation and progress before making a decision on whether or not to practice radiology as a specialty.
conclusionA significant proportion of the surveyed students perceive AI as a threat to the radiological practice, which impacts their career choice. However, the majority claims to have insufficient knowledge of it and believes more information is needed for decision-making.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.