Work

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

Year: 2025

Type: article

Abstract: 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.

Source: Neutrosophic Optimization and Intelligent Systems

DOI: 10.61356/j.nois.2025.7606

Authors: Maher Khalaf Hussein, Asmaa Alqassab, Lubna Thanoon ALkahla

Institutions: University of Telafer, University of Mosul, Ninevah University

Language: English

Topic: Artificial Intelligence in Healthcare and Education

Subfield: Health Informatics

Field: Medicine

Domain: Health Sciences

Open Access status: hybrid

OpenAlex ID: W4414762189

FWCI:

Cites:

Cited by:

Related to: