ArticleInternational wound journal2026
Using Artificial Intelligence-Enabled Digital Health Tools for Wound Management: A Scoping Review.
Article in International wound journal, 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
5 authors.
Funding
Abstract
The aim of this scoping review was to map the existing evidence on artificial intelligence-enabled digital health tools used for wound assessment and documentation, with a particular focus on their feasibility, sustainability, and integration into clinical practice. The review followed Joanna Briggs Institute methodology, and findings were reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews guideline. Searches of MEDLINE, CINAHL, Embase, Scopus, and grey literature were undertaken. Following screening, 11 studies met the inclusion criteria. Artificial intelligence-enabled technologies supported automated wound measurement, wound imaging, digital documentation, longitudinal monitoring, and clinical decision support across a range of clinical settings. Validation studies demonstrated good agreement with conventional wound measurement methods, while implementation studies suggested these technologies were feasible across a range of clinical settings. However, evidence relating to long-term sustainability, interoperability with electronic health record systems, and routine implementation was limited. Overall, artificial intelligence-enabled wound assessment and documentation technologies are transitioning from technical innovation towards broader clinical application. Future research should prioritise longitudinal implementation studies examining sustainability, interoperability, and scalability to support successful integration into routine healthcare delivery.
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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.