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Review

Nanostructures for Biosensing, with a Brief Overview on Cancer Detection, IoT, and the Role of Machine Learning in Smart Biosensors

1
Department of Electrical & Computer Engineering, University of Utah, Salt Lake City, UT 84112, USA
2
Department of Condensed Matter Physics and Materials Sciences, S.N. Bose National Centre for Basic Sciences, Kolkata 700106, India
*
Authors to whom correspondence should be addressed.
Academic Editor: José Miguel García
Sensors 2021, 21(4), 1253; https://doi.org/10.3390/s21041253
Received: 7 January 2021 / Revised: 4 February 2021 / Accepted: 7 February 2021 / Published: 10 February 2021
(This article belongs to the Special Issue Polymeric Chemosensors)
Biosensors are essential tools which have been traditionally used to monitor environmental pollution and detect the presence of toxic elements and biohazardous bacteria or virus in organic matter and biomolecules for clinical diagnostics. In the last couple of decades, the scientific community has witnessed their widespread application in the fields of military, health care, industrial process control, environmental monitoring, food-quality control, and microbiology. Biosensor technology has greatly evolved from in vitro studies based on the biosensing ability of organic beings to the highly sophisticated world of nanofabrication-enabled miniaturized biosensors. The incorporation of nanotechnology in the vast field of biosensing has led to the development of novel sensors and sensing mechanisms, as well as an increase in the sensitivity and performance of the existing biosensors. Additionally, the nanoscale dimension further assists the development of sensors for rapid and simple detection in vivo as well as the ability to probe single biomolecules and obtain critical information for their detection and analysis. However, the major drawbacks of this include, but are not limited to, potential toxicities associated with the unavoidable release of nanoparticles into the environment, miniaturization-induced unreliability, lack of automation, and difficulty of integrating the nanostructured-based biosensors, as well as unreliable transduction signals from these devices. Although the field of biosensors is vast, we intend to explore various nanotechnology-enabled biosensors as part of this review article and provide a brief description of their fundamental working principles and potential applications. The article aims to provide the reader a holistic overview of different nanostructures which have been used for biosensing purposes along with some specific applications in the field of cancer detection and the Internet of things (IoT), as well as a brief overview of machine-learning-based biosensing. View Full-Text
Keywords: nanostructures; biosensor; cancer detection; machine learning nanostructures; biosensor; cancer detection; machine learning
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MDPI and ACS Style

Banerjee, A.; Maity, S.; Mastrangelo, C.H. Nanostructures for Biosensing, with a Brief Overview on Cancer Detection, IoT, and the Role of Machine Learning in Smart Biosensors. Sensors 2021, 21, 1253. https://doi.org/10.3390/s21041253

AMA Style

Banerjee A, Maity S, Mastrangelo CH. Nanostructures for Biosensing, with a Brief Overview on Cancer Detection, IoT, and the Role of Machine Learning in Smart Biosensors. Sensors. 2021; 21(4):1253. https://doi.org/10.3390/s21041253

Chicago/Turabian Style

Banerjee, Aishwaryadev, Swagata Maity, and Carlos H. Mastrangelo. 2021. "Nanostructures for Biosensing, with a Brief Overview on Cancer Detection, IoT, and the Role of Machine Learning in Smart Biosensors" Sensors 21, no. 4: 1253. https://doi.org/10.3390/s21041253

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