2023
DOI: 10.1109/access.2023.3248683
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Memristive Biosensors for Cancer Biomarkers Detection: A Review

Abstract: Detecting cancer biomarkers at an early stage at the clinical level has been the interest of numerous researchers over the years due to its impact on recovery. Therefore, attention is towards fabricating reliable, cost-effective, reproducible, and accurate devices for point-of-care screening. This review aims to highlight the emerging field of memristive biosensors and compare it to similar electrochemical devices used for cancer biomarker detection. The limit of detection (LOD) achieved by memristive biosenso… Show more

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Cited by 7 publications
(4 citation statements)
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“…They can be utilized in biosensors and diagnostic technologies, interacting with biomolecules to enable highsensitivity early cancer detection and rapid virus diagnosis. 11 Additionally, memristors show great potential in the domain of neural computing and brain-machine interfaces, facilitating the construction of neuromorphic computing systems to simulate brain information processing and learning mechanisms. 12 A memristor is a non-linear two-terminal device, and its resistance varies as the input current or voltage accumulates.…”
Section: Chuan Yangmentioning
confidence: 99%
“…They can be utilized in biosensors and diagnostic technologies, interacting with biomolecules to enable highsensitivity early cancer detection and rapid virus diagnosis. 11 Additionally, memristors show great potential in the domain of neural computing and brain-machine interfaces, facilitating the construction of neuromorphic computing systems to simulate brain information processing and learning mechanisms. 12 A memristor is a non-linear two-terminal device, and its resistance varies as the input current or voltage accumulates.…”
Section: Chuan Yangmentioning
confidence: 99%
“…For our device, the linearity of synaptic plasticity for Y8.03 is close to perfect linearity, and the nonlinearity value is calculated to be 0.949 for potentiation and 0.984 for depression, as shown in Figure S8 (Supporting Information), while Y1.74 exhibited a much higher nonlinearity of 5.964/0.829 for potentiation/depression, respectively. [42,43] Perfect linearity represents a nonlinearity value of 1. Furthermore, low power consumption, which is essential for neuromorphic computing, is accomplished using outstanding synaptic characteristics.…”
Section: Application To Artificial Synapse Device Of Ysh-based Egfetmentioning
confidence: 99%
“…In all cases the time derivative of the charge gradient is a function with the parameters of the memristor [120]. Memristors can be applied in the synaptic contacts [129] [130], and other memory applications like neuronal calculations [131], perspiration processes [132] and biosensors [133]. Microtubules composed of tubulin dimers are show also memristor effects [134].…”
Section: A Szasz Open Journal Of Biophysicsmentioning
confidence: 99%