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. 2022 Jun 28;22:220. doi: 10.1186/s12935-022-02640-9

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© The Author(s) 2022

Open AccessThis 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/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

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Fig. 2 — Potential clinical applications for the diagnosis of A pancreatic cancer, including B new biomarkers, C Artificial intelligence (AI), and D nanomaterias. As shown in Part B, samples were obtained from urine, blood, saliva, and feces such as B-1; new biomarkers included DNA methylation such as B-2, proteomic biomarkers such as B-3, and noncoding RNAs such as B-4. AI is shown in Part C. AI utilization can be used in imaging such as C-2, pathology such as C-3 and recognition of biomarkers such as C-4 for PC detection. Part of D describes the application of nanomaterials for the diagnosis of PC; they can play a role as contrast agents such as D-2, diagnostic probes such as D-3, and sensitizers of biomarkers such as D-4