ICCK Journal of Software Engineering | Volume 2, Issue 1: 52-70, 2026 | DOI: 10.62762/JSE.2025.913699
Abstract
Skin‑disease classification has evolved from simple image recognizers into software‑driven pipelines that demand reliability, reproducibility, and ethical governance. While most AI reviews focus on algorithmic accuracy, few examine these systems through a software‑engineering (SE) lens—essential for assessing pipeline modularity, version control, deployment readiness, and long‑term maintainability, all critical for clinical integration. This review surveys literature from 2015 to early 2025, curating about 180 papers that link skin‑disease classification with SE practices. It traces the shift from handcrafted feature‑based classifiers to end‑to‑end convolutional, ensemble,... More >
Graphical Abstract