Development and evaluation of deep learning algorithms for assessment of acute burns and the need for surgery.

ABSTRACT: Assessment of burn extent and depth are critical and require very specialized diagnosis. Automated image-based algorithms could assist in performing wound detection and classification. We aimed to develop two deep-learning algorithms that respectively identify burns, and classify whether they require surgery. An additional aim assessed the performances in different Fitzpatrick skin types. Annotated burn (n = 1105) and background (n = 536) images were collected. Using a commercially available platform for deep learning algorithms, two models were trained and validated on 70% of the images and tested on the remaining 30%. Accuracy was measured for each image using the percentage of wound area correctly identified and F1 scores for the wound identifier; and area under the receiver operating c

SUBMITTER: Boissin C 

PROVIDER: S-EPMC9889389 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature