Wound image and transcriptome datasets of swine acute wounds

Wound healing progresses through overlapping phases: hemostasis,
inflammation, proliferation, and remodeling. Continuous characterization
of these transitions remains limited. Here, we employed a swine excisional
wound model to monitor cellular dynamics across the healing timeline. Both
non-invasive imaging and wound biopsy samples from the wound edge and
center were acquired. Wound photographs were analyzed using advanced
artificial intelligence methods. Wound biopsy samples were subject to RNA
sequencing to generate gene expression profiles for the course of healing.
By combining the image and the gene expression analyses, we were able to
create the comprehensive data for wound healing, which can serve as ground
truth for building wound diagnostic and treatment algorithms.