Learning entities from narratives of skin cancer (LENS) is an automatic entity recognition system built on colloquial writings from skin cancer-related Reddit forums. LENS encapsulates a comprehensive set of 24 labels that address clinical, demographic, and psychosocial aspects of skin cancer. Furthermore, we release LENS as a PyPI and pip package, making it easy for developers to download and install, and also provide a web application that allows users to get model predictions interactively, useful for researchers and individuals with minimal programming experience. Additionally, we publish the annotation guidelines designed specifically for spontaneous skin cancer narratives, that can be implemented to better understand and address challenges when developing corpora or systems for similar diseases. The model achieves an overall entity-level F1 score of 0.561, with notable performance for entities such as “CANC_T” (0.747), “STG” (0.788), “POB” (0.714), “GENDER” (0.750), “A/G” (0.714), and “PPL” (0.703). Other entities with significant results include “TRT” (0.625), “MED” (0.606), “AGE” (0.646), “EMO” (0.619), and “MHD” (0.5). We believe that LENS can serve as an essential tool supporting the analysis of patient discussions leading to improvements in the design and development of modern smart healthcare technologies.