Smartphone-based platforms implementing microfluidic detection with image-based artificial intelligence
Bangfeng Wang,Yiwei Li,Mengfan Zhou,Yulong Han,Mingyu Zhang,Zhaolong Gao,Zetai Liu,Peng Chen,Wei Du,Jing Zhang,Xiao Jun Feng,Bi-Feng Liu +11 more
TL;DR: In this article , the authors summarize recent progress in mobile health platforms, including the aspects of microfluidic chips, imaging modalities, supporting components, and the development of software algorithms.
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Abstract: 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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References
A low-cost, automated parasite diagnostic system via a portable, robotic microscope and deep learning.
TL;DR: A cost‐effective, automated parasite diagnostic system that does not require special sample preparation or a trained user to be developed and was used to conveniently quantify drug response over time in a single animal, showing residual disease due to Anthelmintic resistance after 2 weeks.
38
In Situ Forming Epidermal Bioelectronics for Daily Monitoring and Comprehensive Exercise.
Hao Tang,Yanping Li,Baiqi Chen,Xing Chen,Yu Long Han,Min Guo,Hongqi Xia,Rong Song,Jing Zhang,Jianhua Joe Zhou +9 more
TL;DR: In this paper , the authors proposed in situ forming hydrogel electrodes or electronics (ISF-HEs) that can establish highly conformal interfaces on curved biological surfaces without auxiliary adhesions.
37
Multi-reagents dispensing centrifugal microfluidics for point-of-care testing.
Yujin Xiao,Shunji Li,Zhengbin Pang,Chao Wan,Lina Li,Huijuan Yuan,Xianzhe Hong,Wei Du,Xiao Jun Feng,Yiwei Li,Peng Chen,Bi-Feng Liu +11 more
TL;DR: In this paper , the authors demonstrate a novel multi-reagents dispensing centrifugal microfluidics (MDCM) that allows rapid and automated dispensing of multiple reagents and samples with high throughput and accuracy.
37
Protein binding kinetics quantification via coupled plasmonic-photonic resonance nanosensors in generic microplate reader
TL;DR: The kinetic association and dissociation constants of protein interactions in the authors' sensor plate wells are determined by time-lapse dynamic OD value measurement in the generic microplate reader, enabling SPR-like measurement of protein binding kinetics is now available using generic microplates ubiquitous in many chemistry and biomedical research labs.
36
Chip-Based High-Dimensional Optical Neural Network
TL;DR: In this paper , a dual-layer ONN with Mach-Zehnder interferometer (MZI) network and nonlinear layer is presented, where the nonlinear activation function is achieved by optical-electronic signal conversion.