ArticleJMIR medical education2024
The Potential of Artificial Intelligence Tools for Reducing Uncertainty in Medicine and Directions for Medical Education.
Article in JMIR medical education, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
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
10 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Telemedicine and artificial intelligence in family medicine practice: a systematic review and meta-analysis of barriers and enablers in routine primary care.Frontiers in digital health · 2026Pooled it
- Framework for AI integration into the undergraduate medical curricula: a scoping review.BMC medical education · 2026Article
- Clarifying Molecular Mechanisms and Novel Strategies for Intervention of Uremia and Cognitive Decline.Kidney & blood pressure research · 2026Review
- Clinical Reasoning Uncertainty in Veterinary Medical Encounters with a Clinical Example.Veterinary sciences · 2025Review
- Generative artificial intelligence for general practice; new potential ahead, but are we ready?The European journal of general practice · 2025Article
- From lecture hall to clinic: dental students' AI readiness and anxiety across educational stages.BMC medical education · 2025Article
- Preparing Allergists to Practice in 2050 Using Artificial Intelligence.The journal of allergy and clinical immunology. In practice · 2025Review
- Translation and psychometric validation of the Medical Artificial Intelligence Readiness Scale (MAIRS-MS) for Chinese medical students.BMC nursing · 2025Article
- Application and ethical implication of generative artificial intelligence in medical education: a cross-sectional study among critical care academic physicians in China.BMC medical education · 2025Article
- Readiness to Embrace Artificial Intelligence Among Medical Students in Saudi Arabia: A National Survey.Healthcare (Basel, Switzerland) · 2024Article
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
Abstract
Unlabelled: In the field of medicine, uncertainty is inherent. Physicians are asked to make decisions on a daily basis without complete certainty, whether it is in understanding the patient's problem, performing the physical examination, interpreting the findings of diagnostic tests, or proposing a management plan. The reasons for this uncertainty are widespread, including the lack of knowledge about the patient, individual physician limitations, and the limited predictive power of objective diagnostic tools. This uncertainty poses significant problems in providing competent patient care. Research efforts and teaching are attempts to reduce uncertainty that have now become inherent to medicine. Despite this, uncertainty is rampant. Artificial intelligence (AI) tools, which are being rapidly developed and integrated into practice, may change the way we navigate uncertainty. In their strongest forms, AI tools may have the ability to improve data collection on diseases, patient beliefs, values, and preferences, thereby allowing more time for physician-patient communication. By using methods not previously considered, these tools hold the potential to reduce the uncertainty in medicine, such as those arising due to the lack of clinical information and provider skill and bias. Despite this possibility, there has been considerable resistance to the implementation of AI tools in medical practice. In this viewpoint article, we discuss the impact of AI on medical uncertainty and discuss practical approaches to teaching the use of AI tools in medical schools and residency training programs, including AI ethics, real-world skills, and technological aptitude.
Indexed as
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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.