Self-supervised artificial intelligence predicts recurrence, metastasis and disease specific death from primary cutaneous squamous cell carcinoma at diagnosis.

ABSTRACT: Primary cutaneous squamous cell carcinoma (cSCC) is responsible for ~10,000 deaths annually in the United States. Stratification of risk of poor outcome (PO) including recurrence, metastasis and disease specific death (DSD) at initial biopsy would significantly impact clinical decision-making during the initial post operative period where intervention has been shown to be most effective. In this multi-institutional study, we developed a state-of-the-art self-supervised deep-learning approach with interpretability power and demonstrated its ability to predict poor outcomes of cSCCs at the time of initial biopsy. By highlighting histomorphological phenotypes, our approach demonstrates that poor differentiation and deep invasion correlate with poor prognosis. Our approach is particularly effi

SUBMITTER: Coudray N 

PROVIDER: S-EPMC10760225 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature