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. 2022 Nov 9;12:19115. doi: 10.1038/s41598-022-22595-1

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© The Author(s) 2022

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

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Schematic of observer study design. The first readings were 176 images without artificial intelligence. Abnormal images are separated first and classified as carotid artery calcification, lymph node calcification, or sialolith. Reading confidence is then expressed on a 1 through 4 confidence scale. The second reading takes place 11 weeks after the first reading, and 176 images, different from the first reading, are read using the AI algorithm. Normal and abnormal images are classified first and then a confidence scale of 1 through 4 is displayed.