A Systematic Review of Artificial Intelligence's Function in the Diagnosis of Lung Cancer (2018–2024)

Authors

• Rokan Hazim Hamad, Department of Biology, Ministry of Education, Director of Kirkuk Education, Kirkuk, Iraq.Follow

Abstract

Lung cancer is a leading cause of cancer-related mortality, often diagnosed at advanced stages. This systematic review explores AI applications in lung cancer diagnosis, focusing on medical imaging, pathology, and genetic analysis. A systematic literature review methodology was employed, analyzing studies from databases such as PubMed, IEEE Xplore, and Scopus (2018–2024). Findings indicate that AI-powered diagnostic models, particularly deep learning techniques, outperform conventional methods in accuracy, sensitivity, and early detection capabilities. However, integration into clinical practice presents challenges, including data privacy concerns, model biases, and regulatory limitations. This review highlights the potential of AI in lung cancer screening and provides insights into future research directions.

Recommended Citation

Hamad, Rokan Hazim (2025) "A Systematic Review of Artificial Intelligence's Function in the Diagnosis of Lung Cancer (2018–2024)," Mesopotamian Journal of Artificial Intelligence in Healthcare: Vol. 3: Iss. 1, Article 2.
DOI: https://doi.org/10.58496/MJAIH/2025/002

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This work is licensed under a Creative Commons Attribution 4.0 International License.