This is the authors' abstract. We don't add key points for this paper.
Artificial intelligence (AI) algorithms, such as convolutional neural networks and transformers, have significantly impacted cancer care. For lung cancer, AI holds great potential in addressing smoking cessation, personalized screening, and imaging genomics. And these data could be incorporated to optimize treatment selection. This review highlights the transformative impact of AI in lung cancer management, discusses crucial barriers such as model bias and fairness, and outlines future directions for clinical application.
Answers are grounded in this paper and cite their sources.
No takes yet. Share an insight, caveat, or question.
Muneer et al. (2025) studied this question.
Synapse has enriched 10 related papers. Consider them for comparative context: