Deep Learning in Medical Systems: A Comprehensive Review of Applications and Ethical Challenges

Deep learning (DL) has revolutionized medical systems, enabling unprecedented advancements in diagnostics, treatment personalization, and operational efficiency. This review synthesizes the state-of-the-art applications of DL in healthcare, including medical imaging, clinical decision support, genomics, and drug discovery. Concurrently, it critically examines the ethical challenges—bias, transparency, privacy, and accountability—that threaten equitable and trustworthy deployment. Drawing from 85+ seminal studies, we identify a critical gap: while technical capabilities surge, ethical governance lags. We propose a framework for responsible DL integration in healthcare, emphasizing interdisciplinary collaboration and robust regulatory oversight.