Pancreatic cancer is one of the most lethal gastrointestinal malignancies. Despite advances in cross-sectional imaging, chemotherapy, radiation therapy, and surgical techniques, the 5-year overall survival is only 12%. With the advent and rapid adoption of AI across all industries, we present a review of applications of DL in the care of patients diagnosed with PC. A review of different DL techniques with applications across diagnosis, management, and monitoring is presented across the different pathological subtypes of pancreatic cancer. This systematic review highlights AI as an emerging technology in the care of patients with pancreatic cancer.

Chronic wounds present a large burden to our healthcare system and are typically marked by a failure to transition out of the inflammatory phase of wound healing. Venous leg ulcers (VLUs) represent the largest portion of chronic wounds. A pilot study of eleven (11) patients with VLUs seen over a 12-week period was undertaken utilizing RNA sequencing of wound biopsies and plasma cytokine levels to determine if biomarkers could be identified that would distinguish between wounds which heal versus those that do not. Chronic wounds were found to have increased expression of genes relating to epithelial-to-mesenchymal transition (EMT), cartilage and bone formation, and regulation of apical junction. Plasma cytokine levels showed predictive potential for IL-15 and RANTES, which were found to increase over time in patients with healed wounds. Further research is needed to validate these biomarkers as well as additional study of other chronic wound models, such as diabetic foot ulcers (DFUs).