ArticleInternational wound journal2022
Clinical validation of an artificial intelligence-enabled wound imaging mobile application in diabetic foot ulcers.
Article in International wound journal, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers, 3 of them syntheses that pooled it.
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Who cites it
35 citing papers in PubMed, 3 syntheses or guidelines pooled it, 63 citations in OpenAlex.
- Examining the Role of AI in Changing the Role of Nurses in Patient Care: Systematic Review.JMIR nursing · 2025Pooled it
- Artificial Intelligence Methods for Diagnostic and Decision-Making Assistance in Chronic Wounds: A Systematic Review.Journal of medical systems · 2025Pooled it
- Applications of Artificial Intelligence in Nursing Care: A Systematic Review.Journal of nursing management · 2023Pooled it
- AI-Based Wound Measurement in a Telemedicine-Style Workflow: Agreement With In-Person Reference Measurements Compared With Individual Physicians and Expert Consensus.International wound journal · 2026Article
- Using Artificial Intelligence-Enabled Digital Health Tools for Wound Management: A Scoping Review.International wound journal · 2026Article
- AI-Based Models for Diabetic Foot Ulcer Assessment: Scoping Review.JMIR diabetes · 2026Review
- Computer vision applications in vascular surgery: a systematic review and critical appraisal.NPJ digital medicine · 2026Article
- Validation of a Trained AI Imaging Model for Detecting Diabetic Foot Deformities.International wound journal · 2026Article
- Proposed dense variational autoencoder model integrated with contrastive learning for foot ulcer classification.Scientific reports · 2026Article
- Advancing diabetic foot ulcer therapy: structure-activity relationship approaches for combating reactive oxygen species.Molecular biology reports · 2025Review
- Advancements in Wearable and Implantable BioMEMS Devices: Transforming Healthcare Through Technology.Micromachines · 2025Review
- Artificial Intelligence as a Tool for Self-Care in Patients with Type 1 and Type 2 Diabetes-An Integrative Literature Review.Healthcare (Basel, Switzerland) · 2025Review
- Advancing Diabetic Foot Ulcer Care: AI and Generative AI Approaches for Classification, Prediction, Segmentation, and Detection.Healthcare (Basel, Switzerland) · 2025Review
- Advancements in Wound Dressing Materials: Highlighting Recent Progress in Hydrogels, Foams, and Antimicrobial Dressings.Gels (Basel, Switzerland) · 2025Review
- Screening and monitoring of diabetic polyneuropathy in clinical practice: present and future with connected devices.Frontiers in neurology · 2025Article
- Current status, challenges, and prospects of artificial intelligence applications in wound repair theranostics.Theranostics · 2025Review
- Artificial intelligence's suggestions for level of amputation in diabetic foot ulcers are highly correlated with those of clinicians, only with exception of hindfoot amputations.International wound journal · 2024Article
- Research hotspots and trends in nursing for diabetic foot ulcers: A bibliometric analysis from 2013 to 2023.Heliyon · 2024Review
- Mobile Apps for Wound Assessment and Monitoring: Limitations, Advancements and Opportunities.Journal of medical systems · 2024Review
- Development of an explainable artificial intelligence model for Asian vascular wound images.International wound journal · 2024Article
Corrections and comments
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Authors and funding
12 authors at 1 institution in 1 country.
Funding
Abstract
There is a lifetime risk of 15% to 25% of development of diabetic foot ulcers (DFUs) in patients with diabetes mellitus. DFUs need to be followed up on and assessed for development of complications and/or resolution, which was traditionally performed using manual measurement. Our study aims to compare the intra- and inter-rater reliability of an artificial intelligence-enabled wound imaging mobile application (CARES4WOUNDS [C4W] system, Tetsuyu, Singapore) with traditional measurement. This is a prospective cross-sectional study on 28 patients with DFUs from June 2020 to January 2021. The main wound parameters assessed were length and width. For traditional manual measurement, area was calculated by overlaying traced wound on graphical paper. Intra- and inter-rater reliability was analysed using intra-class correlation statistics. A value of <0.5, 0.5-0.75, 0.75-0.9, and >0.9 indicates poor, moderate, good, and excellent reliability, respectively. Seventy-five wound episodes from 28 patients were collected and a total of 547 wound images were analysed in this study. The median wound area during the first clinic consultation and all wound episodes was 3.75 cm
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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.