AIMC Topic: Electrochemical Techniques
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Role of Machine Learning Assisted Biosensors in Point-of-Care-Testing For Clinical Decisions.
ACS sensors
Aug 15, 2024
Point-of-Care-Testing (PoCT) has emerged as an essential component of modern healthcare, providing rapid, low-cost, and simple diagnostic options. The integration of Machine Learning (ML) into biosensors has ushered in a new era of innovation in the ...
CRISPR-Enhanced Photocurrent Polarity Switching for Dual-lncRNA Detection Combining Deep Learning for Cancer Diagnosis.
Analytical chemistry
Aug 2, 2024
Abnormal expression in long noncoding RNAs (lncRNAs) is closely associated with cancers. Herein, a novel CRISPR/Cas13a-enhanced photocurrent-polarity-switching photoelectrochemical (PEC) biosensor was engineered for the joint detection of dual lncRNA...
Enhancing electrochemical detection through machine learning-driven prediction for canine mammary tumor biomarker with green silver nanoparticles.
Analytical and bioanalytical chemistry
Jul 20, 2024
This study developed an innovative biosensor strategy for the sensitive and selective detection of canine mammary tumor biomarkers, cancer antigen 15-3 (CA 15-3) and mucin 1 (MUC-1), integrating green silver nanoparticles (GAgNPs) with machine learni...
Machine learning trained poly (3,4-ethylenedioxythiophene) functionalized carbon matrix suspended Cu nanoparticles for precise monitoring of nitrite from pickled vegetables.
Food chemistry
Jul 17, 2024
Precise monitoring of nitrite from real samples has gained significant attention due to its detrimental impact on human health. Herein, we have fabricated poly(3,4-ethylenedioxythiophene) functionalized carbon matrix suspended Cu nanoparticles (PEDOT...
Au-decorated TiCT/porous carbon immunoplatform for ECM1 breast cancer biomarker detection with machine learning computation for predictive accuracy.
Talanta
Jul 4, 2024
Electrochemical immunosensors, surpassing conventional diagnostics, exhibit significant potential for cancer biomarker detection. However, achieving a delicate balance between signal sensitivity and operational stability, especially at the heterostru...
Deep Learning Enhanced Label-Free Action Potential Detection Using Plasmonic-Based Electrochemical Impedance Microscopy.
Analytical chemistry
Jul 2, 2024
Measuring neuronal electrical activity, such as action potential propagation in cells, requires the sensitive detection of the weak electrical signal with high spatial and temporal resolution. None of the existing tools can fulfill this need. Recentl...
Machine learning powered CN-coordinated cobalt nanoparticles embedded cellulosic nanofibers to assess meat quality via clenbuterol monitoring.
Biosensors & bioelectronics
Jun 13, 2024
The World Anti-Doping Agency (WADA) has prohibited the use of clenbuterol (CLN) because it induces anabolic muscle growth while potentially causing adverse effects such as palpitations, anxiety, and muscle tremors. Thus, it is vital to assess meat qu...
Smartphone based wearable sweat glucose sensing device correlated with machine learning for real-time diabetes screening.
Analytica chimica acta
May 21, 2024
BACKGROUND: Diabetes is a significant health threat, with its prevalence and burden increasing worldwide indicating its challenge for global healthcare management. To decrease the disease severity, the diabetic patients are recommended to regularly c...
Electrochemical platform for detecting Escherichia coli bacteria using machine learning methods.
Biosensors & bioelectronics
May 19, 2024
We present an electrochemical platform designed to reduce time of Escherichia coli bacteria detection from 24 to 48-h to 30 min. The presented approach is based on a system which includes gallium-indium (eGaIn) alloy to provide conductivity and a hyd...
Resolution of tonic concentrations of highly similar neurotransmitters using voltammetry and deep learning.
Molecular psychiatry
Apr 25, 2024
With advances in our understanding regarding the neurochemical underpinnings of neurological and psychiatric diseases, there is an increased demand for advanced computational methods for neurochemical analysis. Despite having a variety of techniques ...
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