ArticleJournal of experimental orthopaedics2026
From code to care in hours: Why "go fast and fix things" is the new medical imperative.
Article in Journal of experimental orthopaedics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- Artificial intelligence in orthopaedics should be built with surgeons, not just for them!Journal of experimental orthopaedics · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Recent technological advances in artificial intelligence and machine learning have led to rapid changes in clinical informatics. With the release of new models, the barrier to creating medical software has markedly decreased. As noted in the now-viral article by Matt Shumer, we have moved from a world where building a clinical application took a team of engineers working over the course of months to years, to one where a single clinician can develop and deploy a working prototype in hours to days. However, the same innovation driving this 'explosion' of tools also carries the risk of flooding health systems with unvalidated 'AI slop.' As prohibiting tools developed through AI runs the risk of stifling innovation and limiting potentially impactful discoveries, we suggest abandoning the slow, fear-based resistance to AI adoption. Further, we propose a 'go fast and fix things' framework-utilising target product profiles, regulatory sandboxes, and continuous audit-to harness the speed of generation and prototyping while rigorously validating clinical utility.
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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.