ArticleThe Journal of pathology2025
Advancing homebrew AI in diagnostic practice: opportunities and barriers
Article in The Journal of pathology, 2025. 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.
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0 citing papers in PubMed.
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Authors and funding
2 authors.
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No grant is acknowledged in the PubMed record.
Abstract
In a recent issue of The Journal of Pathology, Calderaro et al present a timely and persuasive argument advocating for the integration of homebrew artificial intelligence (AI) models in diagnostic pathology. Their article is a robust defense of local model development within pathology departments as a pathway to democratizing digital diagnostics. This commentary expands on their premise, critically examining the real-world implications, practical limitations, and unmet needs of practicing pathologists. The commentary outlines both the opportunities and challenges for the widespread adoption of homebrew AI in pathology practice. Without institutional backing, digital infrastructure, and sustained training efforts, the promise of homebrew AI may falter. © 2025 The Author(s). The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.
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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 Socratic graph.