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. 2022 Mar 29;14(7):1729. doi: 10.3390/cancers14071729

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© 2022 by the authors.

Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).

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(A) Tornado diagram showing the impact of input parameters on incremental cost-effectiveness ratio (ICER) in the base case scenario. Assuming a willingness-to-pay threshold of USD 100,000 per QALY, CT + AI remained cost-effective in all cases. (B) Tornado diagram showing the impact of input parameters on incremental cost-effectiveness ratio (ICER) when costs of AI were set to USD 1240 with an expected value of USD 100,000 per QALY. Blue bars show changes when decreasing the value of an input parameter as compared to the base case scenario and red bars when increasing the respective value. Sens = sensitivity; Spec = specificity; CT = computed tomography; AI = artificial intelligence; P = probability.