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. 2021 Jun 17;9(6):e26601. doi: 10.2196/26601

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©José S Enriquez, Yan Chu, Shivanand Pudakalakatti, Kang Lin Hsieh, Duncan Salmon, Prasanta Dutta, Niki Zacharias Millward, Eugene Lurie, Steven Millward, Florencia McAllister, Anirban Maitra, Subrata Sen, Ann Killary, Jian Zhang, Xiaoqian Jiang, Pratip K Bhattacharya, Shayan Shams. Originally published in JMIR Medical Informatics (https://medinform.jmir.org), 17.06.2021.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Medical Informatics, is properly cited. The complete bibliographic information, a link to the original publication on https://medinform.jmir.org/, as well as this copyright and license information must be included.

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Schematic illustrating the concept of leveraging anatomical magnetic resonance imaging (MRI), hyperpolarized magnetic resonance (HP-MR), and artificial intelligence as complementary modalities toward developing actionable biomarkers of pancreatic ductal adenocarcinoma. CNNs: convolutional neural networks; EHR: electronic health record.