ArticleThe clinical teacher2026
The Promises and Perils of Clinical Decision Support Artificial Intelligence.
Article in The clinical teacher, 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
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Evidence-based clinical decision support artificial intelligence (AI) is rapidly expanding, but its safe and effective use depends on rigorous validation, trustworthy evidence sources and careful integration into clinical workflows. Current available systems show strong potential to improve diagnostic accuracy, reduce clinician workload and possibly benefit patient care, but challenges remain before its real-world adoption. We must be responsible in its integration to ensure AI truly strengthens clinical judgment. This article is a viewpoint of AI tools for clinical decision support, addressing a rapidly evolving field and provides insights that are useful for clinicians and educators in clinical settings. When used within appropriate medical training, AI may help augment diagnostic accuracy and improve efficiency. Nevertheless, while AI offers promising features, it also presents ethical and reliability challenges, which may negatively affect the medical professional identity.
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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.