Abstract
Cutaneous squamous cell carcinoma (cSCC) is the second most common skin cancer with rising incidence and mortality. Accurate risk stratification essential to identify high-risk patients and determine appropriate treatment. Histological evaluation of tissue whole slide images (WSI) is the gold-standard for cSCC risk assessment. However, manual tumor localization is tedious due to the large size of WSI and involves human-assessment related variability. We propose an AI-based assistive risk stratification tool for cSCC which performs tumor localization and risk stratification in a reproducible manner ensuring faster turnaround time.
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