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Integrating Nanotechnology And Biosensors For Enhanced Disease Detection

Usha Eswaran, Vivek Eswaran, Keerthna Murali, Vishal  Eswaran

Abstract


The fusion of nanotechnology and biosensors holds tremendous potential for revolutionizing disease detection and monitoring, offering heightened sensitivity and specificity in diagnostic processes. This study presents a comprehensive overview of current research endeavors, delineates existing challenges, and proposes innovative strategies to construct integrated nanotechnology-biosensor platforms, fostering advancements in disease detection. The research methodology adopts a mixed methods approach, encompassing a thorough literature review, experimental design, data collection and analysis, and platform evaluation and validation. This holistic strategy aims to provide a robust foundation for exploring the synergies between nanotechnology and biosensors. By integrating insights from existing literature with empirically derived data, the study seeks to elucidate the current landscape while actively contributing novel perspectives to the field. Anticipated outcomes of this research include the development of highly sensitive and specific integrated sensing platforms. These platforms are expected to yield quantified performance data, showcasing their efficacy in disease detection. Moreover, the study aims to assess the potential impacts of these integrated technologies on precision medicine, paving the way for personalized and targeted therapeutic interventions. The overarching goal of this research is to propel the evolution of biosensor and nanomaterial-based diagnostic technologies. By doing so, the study aspires to make tangible contributions to improving patient outcomes. Through a meticulous examination of the integration of nanotechnology and biosensors, this research seeks to advance our understanding of their combined potential, fostering innovation in diagnostic capabilities and ultimately enhancing the landscape of medical care.

Keywords


nanotechnology, biosensors, disease detection, precision medicine, diagnostics

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References


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DOI: https://doi.org/10.37591/jonsnea.v13i2.1466

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