Clinical validation of an artificial intelligence‐enabled wound imaging mobile application in diabetic foot ulcers

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 0.9 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 cm2 (interquartile range [IQR] 1.40–16.50) and 3.10 cm2 (IQR 0.60–14.84), respectively. There is excellent intra‐rater reliability of C4W on three different image captures of the same wound (intra‐rater reliability ranging 0.933–0.994). There is also excellent inter‐rater reliability between three C4W devices for length (0.947), width (0.923), and area (0.965). Good inter‐rater reliability for length, width, and area (range 0.825–0.934) was obtained between wound nurse measurement and each of the C4W devices. In conclusion, we obtained good inter‐rater and intra‐rater reliability of C4W measurements against traditional wound measurement. The C4W is a useful adjunct in monitoring DFU wound progress.