OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Machine learning toward high-performance electrochemical sensors
Gabriela F. Giordano, Larissa Fernanda Ferreira, Ítalo R. S. Bezerra, et al.
Analytical and Bioanalytical Chemistry (2023) Vol. 415, Iss. 18, pp. 3683-3692
Open Access | Times Cited: 49

Showing 26-50 of 49 citing articles:

Enhancing the Predictive Performance of Molecularly Imprinted Polymer-Based Electrochemical Sensors Using a Stacking Regressor Ensemble of Machine Learning Models
Reza Mohammadi Dashtaki, Saeed Mohammadi Dashtaki, Esmaeil Heydari‐Bafrooei, et al.
ACS Sensors (2025)
Closed Access

Recent Advances in MXene-based Electrochemical Sensors for Healthcare Applications
Harini Loganathan, D. Durgalakshmi, R. Ajay Rakkesh
TrAC Trends in Analytical Chemistry (2025), pp. 118276-118276
Closed Access

Artificial intelligence algorithms-assisted biosensors in the detection of foodborne pathogenic bacteria: Recent advances and future trends
Zhuowen Deng, Yong‐Huan Yun, Nuo Duan, et al.
Trends in Food Science & Technology (2025), pp. 105072-105072
Closed Access

Bioelectroanalytical Technologies for Advancing the Frontiers To Democratize Personalized Desired Health
Susana Campuzano, Víctor Ruiz‐Valdepeñas Montiel, Rebeca M. Torrente‐Rodríguez, et al.
Analytical Chemistry (2025)
Closed Access

Electrochemical Biosensor Arrays for Multiple Analyte Detection
Debashis Sen, Robert A. Lazenby
Analysis & Sensing (2023) Vol. 4, Iss. 2
Closed Access | Times Cited: 9

Recent advances in electrochemical biosensors for the detection of pathogens, diseases biomarkers, and heavy metal ions
Manoj Kumar Goshisht, Goutam Kumar Patra, Aabroo Mahal, et al.
Inorganica Chimica Acta (2024) Vol. 574, pp. 122403-122403
Closed Access | Times Cited: 3

A Machine Learning Approach for Enhanced Glucose Prediction in Biosensors
António Abreu, Daniela Oliveira, Irene Vinagre, et al.
Chemosensors (2025) Vol. 13, Iss. 2, pp. 52-52
Open Access

Pattern Recognition of Neurotransmitters: Complexity Reduction for Serotonin and Dopamine
Ibrahim Moubarak Nchouwat Ndumgouo, Emily DeVoe, Silvana Andreescu, et al.
Biosensors (2025) Vol. 15, Iss. 4, pp. 209-209
Open Access

Machine learning in modeling, analysis and control of electrochemical reactors: A tutorial review
Wenlong Wang, Zhe Wu, Dominic Peters, et al.
Digital Chemical Engineering (2025), pp. 100237-100237
Open Access

Machine Learning-Guided Cobalt@Copper Dual-Metal Electrochemical Sensor for Urinary Creatinine Detection
Keerakit Kaewket, Théo Claude Roland Outrequin, Somrudee Deepaisarn, et al.
ACS Sensors (2025)
Open Access

Electrochemical bioanalysis: All that still hides the tip of the iceberg
Susana Campuzano, José M. Pingarrón
Current Opinion in Electrochemistry (2023) Vol. 41, pp. 101359-101359
Open Access | Times Cited: 6

Strain sensing characteristics of 3D-printed carbon nanotubes/polypyrrole/UV-curable composites: experimental validation and machine learning predictions
Nutthapong Poompiew, Wiwittawin Sukmas, Chuanchom Aumnate, et al.
Progress in Additive Manufacturing (2024)
Closed Access | Times Cited: 2

Strategies to Enrich Electrochemical Sensing Data with Analytical Relevance for Machine Learning Applications: A Focused Review
Mijeong Kang, Donghyeon Kim, Jihee Kim, et al.
Sensors (2024) Vol. 24, Iss. 12, pp. 3855-3855
Open Access | Times Cited: 2

Highly-stable Au-Pd bimetallic nanoparticles decorated violet phosphorene with polyamidoamine dendrimer for ultrasensitive portable sensing of microRNA-319a in rice with machine learning assistance
Yutang Wang, Peng Liu, Qiang Huang, et al.
Sensors and Actuators B Chemical (2024) Vol. 427, pp. 137205-137205
Closed Access | Times Cited: 2

Accurate ion type and concentration detection using two bare electrodes by machine learning of non-faradaic electrochemical impedance measurements of an automated fluidic system
Meral Sağıroğlu, Eda Deniz Demirel, Senol Mutlu
Journal of Electroanalytical Chemistry (2024) Vol. 961, pp. 118256-118256
Closed Access | Times Cited: 1

Electrochemical deposition of HSA on Ag electrode for its quantitative determination using SERS and machine learning
I. A. Boginskaya, E. A. Slipchenko, Robert R. Safiullin, et al.
Sensors and Actuators A Physical (2024) Vol. 377, pp. 115700-115700
Closed Access | Times Cited: 1

Advanced sensor platforms and machine learning tools for real-time contaminant monitoring
Mia Sands, Tehreem Chaudhary, Joseph Irudayaraj, et al.
Elsevier eBooks (2024), pp. 293-320
Closed Access | Times Cited: 1

13Ultrafast Microfluidic Solvent Extraction and Machine Learning-Assisted Impedimetric Sensor for Multidetermination of Scaling Ions in Crude Oils
Alexandre Ataíde da Silva, Ricardo A. G. de Oliveira, Gabriela F. Giordano, et al.
Sensors and Actuators B Chemical (2023) Vol. 403, pp. 135151-135151
Closed Access | Times Cited: 2

Electrochemical-Based Biosensor Platforms in Lab-Chip Models for Point-of-Need Toxicant Analysis
Mohana Marimuthu, V. Krishnan, Shailendra Sudhakaran, et al.
Electrochem (2023) Vol. 4, Iss. 4, pp. 537-552
Open Access | Times Cited: 1

Mechanistic and data-driven modeling of carbon respiration with bio-electrochemical sensors
R Puri, Seyed Aryan Emaminejad, Roland D. Cusick
Current Opinion in Biotechnology (2024) Vol. 88, pp. 103173-103173
Open Access

Comprehensive Electrochemical and Machine Learning-Based Study of Rancidity in Four Edible Oils Over Various Storage Periods
Song Wan, Lin Tang
International Journal of Electrochemical Science (2024), pp. 100799-100799
Open Access

Ultradense Electrochemical Chip and Machine Learning for High-Throughput, Accurate Anticancer Drug Screening
Daniel S. Doretto, Paula C. R. Corsato, C. Silva, et al.
ACS Sensors (2024)
Closed Access

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