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Hyperpolarized Magnetic Resonance and Artificial Intelligence: Frontiers of Imaging in Pancreatic Cancer

Hyperpolarized Magnetic Resonance and Artificial Intelligence: Frontiers of Imaging in Pancreatic Cancer

Zhang et al [99] proposed a tumor detection framework for PDAC using CT. The framework utilized feature pyramid networks with the faster R-CNN model. The Affiliated Hospital of Qingdao University provided a dataset containing 2890 CT images, and a classification AUC of 0.9455 was achieved. This framework outperformed the state-of-the-art methods, but still suffered from input uncertainty inherent in closed-source datasets.

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

JMIR Med Inform 2021;9(6):e26601

Usability Challenges for Health and Wellness Mobile Apps: Mixed-Methods Study Among mHealth Experts and Consumers

Usability Challenges for Health and Wellness Mobile Apps: Mixed-Methods Study Among mHealth Experts and Consumers

Zhang and Adipat [11] also highlighted issues specific to mobile devices, such as the mobile context, hardware limitations, and data-entry challenges as additional considerations not addressed with these models. Despite the increasing willingness of consumers to try m Health apps [12], it is important to understand and appeal to the motivations of the users and decrease barriers to “digital adherence.” User experience research is thus a critical component to the success of m Health apps.

Mei Shan Liew, Jian Zhang, Jovis See, Yen Leng Ong

JMIR Mhealth Uhealth 2019;7(1):e12160