Mapping the use of artificial intelligence for skin injury assessment and care in hospitalized patients: A scoping review.
Background & Aim: Skin injuries are frequent hospital complications, and the role of artificial intelligence in management remains unclear. This review aimed to identify, map, and analyze the evidence on the use of artificial intelligence in the assessment, monitoring, and management of skin injurie...
| Publicado en: | Nursing Practice Today Vol. 13; no. 1; pp. 17 - 32 |
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| Autores principales: | , , , , , , |
| Formato: | research systematic review tables/charts Journal Article |
| Publicado: |
Tehran University of Medical Sciences
2026
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=190435301&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 190435301 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 23831154 JKHN jtl: Nursing Practice Today issn: 23831154 maglogo: N pubinfo: dt: 2026 vid: 13 iid: 1 pid: 21783 pub: Tehran University of Medical Sciences artinfo: ui: 190435301 190435301 190435301 10.18502/npt.v13i1.20595 190435301 ppf: 17 ppct: 15 formats: fmt: @attributes: type: P tig: atl: Mapping the use of artificial intelligence for skin injury assessment and care in hospitalized patients: A scoping review. aug: au: Martins Zanetti, Ângelo Antônio Paulino Desconsi, Denise Lima De Miranda, Rafaella Manhoni Brolacci Lana, Luisa Del Rosso Calache, Lucas Daniel Molina Lima, Silvana Andréa Rodrigues Serafim, Clarita Terra affil: Department of Nursing, Medical School, São Paulo State University, Botucatu, São Paulo, Brazil sug: subj: Artificial Intelligence Utilization Skin Injuries Skin Care Evaluation Wound Care Evaluation Wound Assessment Hospitalization Wounds and Injuries Therapy Digital Health World Health Human Scoping Review Embase Cochrane Library PubMed CINAHL Database Funding Source Pressure Ulcer Therapy Support Vector Machine Boosting Machine Learning Algorithms Decision Support Systems, Clinical Patient Safety Workload ab: Background & Aim: Skin injuries are frequent hospital complications, and the role of artificial intelligence in management remains unclear. This review aimed to identify, map, and analyze the evidence on the use of artificial intelligence in the assessment, monitoring, and management of skin injuries in hospitalized patients worldwide. Methods & Materials: A scoping review was conducted following the Joanna Briggs Institute guidance and the PRISMA Extension for Scoping Reviews (PRISMA-ScR). Searches were carried out in Embase, PubMed, Scopus, CINAHL, Cochrane Library, Web of Science, SciELO, BVS, LILACS, and the CAPES thesis and dissertation catalog. Eligible sources included primary studies, technical notes, dissertations, and theses. All references were organized in EndNote Web and transferred to Rayyan to support duplicate removal and facilitate screening by reviewers. Results: The search resulted in the identification of 1,240 studies, of which eight were included and published in English. Most studies are technological development studies with samples ranging from 10 to 5,729 images or participants. Studies have shown that artificial intelligence techniques applied to pressure injuries, including Convolutional Neural Networks, Random Forest, Support Vector Machine, and Extreme Gradient Boosting, improve detection, measurement, classification, risk prediction, and clinical decision support, potentially reducing workload and enhancing care safety. Conclusion: The application of artificial intelligence in the domain of skin injuries revealed a variety of uses. However, it was predominantly focused on the specific context of pressure injuries in hospitalized individuals. Consequently, a noticeable gap in the literature was identified regarding alternative categories of injuries affecting this population segment. pubtype: Academic Journal doctype: research systematic review tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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