Smartphone-based platforms implementing microfluidic detection with image-based artificial intelligence

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作者
Bangfeng Wang
Yiwei Li
Mengfan Zhou
Yulong Han
Mingyu Zhang
Zhaolong Gao
Zetai Liu
Peng Chen
Wei Du
Xingcai Zhang
Xiaojun Feng
Bi-Feng Liu
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[1] Huazhong University of Science and Technology,The Key Laboratory for Biomedical Photonics of MOE at Wuhan National Laboratory for Optoelectronics
[2] Harvard University, Hubei Bioinformatics & Molecular Imaging Key Laboratory, Systems Biology Theme, Department of Biomedical Engineering, College of Life Science and Technology
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The frequent outbreak of global infectious diseases has prompted the development of rapid and effective diagnostic tools for the early screening of potential patients in point-of-care testing scenarios. With advances in mobile computing power and microfluidic technology, the smartphone-based mobile health platform has drawn significant attention from researchers developing point-of-care testing devices that integrate microfluidic optical detection with artificial intelligence analysis. In this article, we summarize recent progress in these mobile health platforms, including the aspects of microfluidic chips, imaging modalities, supporting components, and the development of software algorithms. We document the application of mobile health platforms in terms of the detection objects, including molecules, viruses, cells, and parasites. Finally, we discuss the prospects for future development of mobile health platforms.
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