ArticleCureus2026
Insights From Michael Polanyi: Tacit Knowledge and Its Critical Importance in Medical Education.
Article in Cureus, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
With the onset of the Fourth Industrial Revolution (the digital age), medical education is undergoing dramatic change. Artificial intelligence (AI) and machine learning (ML) have driven an increase in virtual learning sessions and meetings. Bedside teaching is increasingly at risk of becoming an endangered mode of education. Tacit knowledge, as defined and explained by Michael Polanyi, relies heavily on direct interaction with a teacher and mentor. The question, therefore, arises, "Can artificial intelligence and machine learning function as meaningful adjuncts that support the transfer of tacit knowledge in medical education, or will bedside teaching ultimately be replaced entirely by machine learning and artificial intelligence?"
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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.