AIMC Topic: Electrochemical Techniques

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Electrochemical biosensing in oncology: a review advancements and prospects for cancer diagnosis.

Cancer biology & therapy
Early and precise diagnosis of cancer is pivotal for effective therapeutic intervention. Traditional diagnostic methods, despite their reliability, often face limitations such as invasiveness, high costs, labor-intensive procedures, extended processi...

Application of Machine Learning for FOS/TAC Soft Sensing in Bio-Electrochemical Anaerobic Digestion.

Molecules (Basel, Switzerland)
This study explores the application of various machine learning (ML) models for the real-time prediction of the FOS/TAC ratio in microbial electrolysis cell anaerobic digestion (MEC-AD) systems using data collected during a 160-day trial treating bre...

Back Propagation Artificial Neural Network Enhanced Accuracy of Multi-Mode Sensors.

Biosensors
The detection of small molecules is critical in many fields, but traditional electrochemical detection methods often exhibit limited accuracy. The construction of multi-mode sensors is a common strategy to improve detection accuracy. However, most ex...

Neural Network-Enhanced Electrochemical/SERS Dual-Mode Microfluidic Platform for Accurate Detection of Interleukin-6 in Diabetic Wound Exudates.

Analytical chemistry
Interleukin-6 (IL-6) plays a pivotal role in the inflammatory response of diabetic wounds, providing critical insights for clinicians in the development of personalized treatment strategies. However, the low concentration of IL-6 in biological sample...

Leaf-Face Classifier Based on an Integrated Electrochemical Tongue and Machine Learning.

ACS sensors
Botanical sourcing seriously impacts the safety and potency of herbal medicines, restricting the development of the traditional Chinese medicinal industry. Rapid and convenient identification of plant resources is important to address this problem. H...

Using Machine Learning to Design a FeMOF Bidirectional Regulator for Electrochemiluminescence Sensing of Tau Protein.

ACS applied materials & interfaces
The single-luminophore-based ratiometric electrochemiluminescence (ECL) sensor coupling bidirectional regulator has become a research hotspot in the detection field because of its simplicity and accuracy. However, the limited bidirectional regulator ...

Artificial-Intelligence Bio-Inspired Peptide for Salivary Detection of SARS-CoV-2 in Electrochemical Biosensor Integrated with Machine Learning Algorithms.

Biosensors
Developing affordable, rapid, and accurate biosensors is essential for SARS-CoV-2 surveillance and early detection. We created a bio-inspired peptide, using the SAGAPEP AI platform, for COVID-19 salivary diagnostics via a portable electrochemical dev...

Quantification of L-lactic acid in human plasma samples using Ni-based electrodes and machine learning approach.

Talanta
This work presents a robust strategy for quantifying overlapping electrochemical signatures originating from complex mixtures and real human plasma samples using nickel-based electrochemical sensors and machine learning (ML). This strategy enables th...

ECLStat: A robust machine learning based visual imaging tool for electrochemiluminescence biosensing.

Computers in biology and medicine
Visual electrochemiluminescence (ECL) has emerged as a prominent diagnostic method for accurately quantifying various disease markers even at point of care setting with high sensitivity and accuracy. It does not employ complicated instruments such as...

Selectively Quantify Toxic Pollutants in Water by Machine Learning Empowered Electrochemical Biosensors.

Environmental science & technology
Electroactive biofilm (EAB) sensors have become pivotal in water quality detection and early ecological risk warnings due to their remarkable sensitivity. However, it is challenging to identify multiple toxicants in complex water bodies concurrently....