A primer on artificial intelligence in pancreatic imaging

Artificial Intelligence (AI) is set to transform medical imaging by leveraging the vast data contained in medical images. Deep learning and radiomics are the two main AI methods currently being applied within radiology. Deep learning uses a layered set of self-correcting algorithms to develop a mathematical model that best fits the data. Radiomics converts imaging data into mineable features such as signal intensity, shape, texture, and higher-order features. Both methods have the potential to improve disease detection, characterization, and prognostication. This article reviews the current status of artificial intelligence in pancreatic imaging and critically appraises the quality of existing evidence using the radiomics quality score. & COPY; 2023 Societe francaise de radiologie. Published by Elsevier Masson SAS. All rights reserved.

Automated summary

Artificial Intelligence (AI) is transforming medical imaging by utilizing the abundant data in medical images. The two main AI methods currently applied in radiology are deep learning and radiomics. Deep learning uses self-correcting algorithms to develop a mathematical model that best fits the data, while radiomics converts imaging data into mineable features. Both methods have the potential to enhance disease detection, characterization, and prognostication. This article reviews the current state of AI in pancreatic imaging and evaluates the quality of existing evidence using the radiomics quality score. © 2023 Societe francaise de radiologie. Published by Elsevier Masson SAS. All rights reserved.