The DOI matches its Crossref record; 186 of the 186 references it cites were found in a registry or an index.
Nanomaterials for Healthcare Biosensing Applications
Open accessAbstract
In recent years, an increasing number of nanomaterials have been explored for their applications in biomedical diagnostics, making their applications in healthcare biosensing a rapidly evolving field. Nanomaterials introduce versatility to the sensing platforms and may even allow mobility between different detection mechanisms. The prospect of a combination of different nanomaterials allows an exploitation of their synergistic additive and novel properties for sensor development. This paper covers more than 290 research works since 2015, elaborating the diverse roles played by various nanomaterials in the biosensing field. Hence, we provide a comprehensive review of the healthcare sensing applications of nanomaterials, covering carbon allotrope-based, inorganic, and organic nanomaterials. These sensing systems are able to detect a wide variety of clinically relevant molecules, like nucleic acids, viruses, bacteria, cancer antigens, pharmaceuticals and narcotic drugs, toxins, contaminants, as well as entire cells in various sensing media, ranging from buffers to more complex environments such as urine, blood or sputum. Thus, the latest advancements reviewed in this paper hold tremendous potential for the application of nanomaterials in the early screening of diseases and point-of-care testing.
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Cites
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Cited by
Significance of nanomaterials in electrochemical glucose sensors: An updated review (2016-2020)
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Self-citationAnoob, F., Arachchi, S., Azamathulla, H. M., Al-mahbashi, N., & Rathnayake, U. (2024) · Case Studies in Chemical and Environmental Engineering · doi:10.1016/j.cscee.2024.100639 · Cited by 42
Metadata
- Authors
- Pirzada, M., & Altintas, Z.
- Venue
- Sensors
- Publisher
- MDPI AG
- Published
- 2019-12-02
- Volume
- 19
- Issue
- 23
- Pages
- 5311
- ISSN
- 1424-8220 (ISSN-L)
- OpenAlex
- W2990971121
- Cited by
- 253
- References
- 186
- FWCI
- 7.81
- 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).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.