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Evaluating risk models and AI in managing pulmonary nodules
Matthew Smeltzer, PhD, University of Memphis, Memphis, TN, discusses findings from a large cohort of pulmonary nodules in the mid-south United States, identified through non-screening methods. He comments on the feasibility of applying automated risk prediction models to manage lung nodules, noting that these models were only applicable in less than 50% of cases. Ongoing debates about artificial intelligence (AI)-based imaging methods raise questions about whether they could complement or outperform traditional risk models, highlighting the need for better strategies to manage the growing detection of pulmonary nodules. This interview took place at the 2024 World Conference on Lung Cancer (WCLC) in San Diego, CA.
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