The DOI matches its Crossref record; 156 of the 156 references it cites were found in a registry or an index.
Microfluidic Point-of-Care (POC) Devices in Early Diagnosis: A Review of Opportunities and Challenges
Open accessAbstract
The early diagnosis of infectious diseases is critical because it can greatly increase recovery rates and prevent the spread of diseases such as COVID-19; however, in many areas with insufficient medical facilities, the timely detection of diseases is challenging. Conventional medical testing methods require specialized laboratory equipment and well-trained operators, limiting the applicability of these tests. Microfluidic point-of-care (POC) equipment can rapidly detect diseases at low cost. This technology could be used to detect diseases in underdeveloped areas to reduce the effects of disease and improve quality of life in these areas. This review details microfluidic POC equipment and its applications. First, the concept of microfluidic POC devices is discussed. We then describe applications of microfluidic POC devices for infectious diseases, cardiovascular diseases, tumors (cancer), and chronic diseases, and discuss the future incorporation of microfluidic POC devices into applications such as wearable devices and telemedicine. Finally, the review concludes by analyzing the present state of the microfluidic field, and suggestions are made. This review is intended to call attention to the status of disease treatment in underdeveloped areas and to encourage the researchers of microfluidics to develop standards for these devices.
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Cites
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Cited by
Cell Migration Assays and Their Application to Wound Healing Assays—A Critical Review
Yang, C., Yin, D., Zhang, H., Badea, I., Yang, S.-M., & Zhang, W. (2024) · Micromachines · doi:10.3390/mi15060720 · Cited by 22
Self-citation
Metadata
- Authors
- Yang, S.-M., Lv, S., Zhang, W., & Cui, Y.
- Venue
- Sensors
- Publisher
- MDPI AG
- Published
- 2022-02-18
- Volume
- 22
- Issue
- 4
- Pages
- 1620
- ISSN
- 1424-8220 (ISSN-L)
- OpenAlex
- W4212772615
- Cited by
- 299
- References
- 156
- FWCI
- 15.65
- Type
- journal article
- Language
- en
- Open access
- gold
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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