Exploring Machine Learning Strategies for Single-Cell Transcriptomic Analysis in Wound Healing
January 2025
in “
Burns & Trauma
”
single-cell RNA sequencing scRNA-seq machine learning fibroblast populations immune cell dynamics scar formation regenerative healing cell clustering trajectory inference immune cell functions spatial organization chronic wounds fibrosis precision medicine regenerative therapies macrophages deep learning transformer models interpretable AI multi-omics
Studysummary This review highlights recent research using single-cell RNA sequencing and machine learning in wound healing, revealing significant insights into fibroblast diversity, immune cell dynamics, and the spatial organization of cells, which may transform therapeutic strategies for chronic wounds, fibrosis, and tissue regeneration.
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