ArticleAnalytical and bioanalytical chemistry2023
Machine learning toward high-performance electrochemical sensors.
Article in Analytical and bioanalytical chemistry, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
31 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Integrating AI with Biosensors and Voltammetry for Neurotransmitter Detection and Quantification: A Systematic Review.Biosensors · 2025Pooled it
- Multifunctional Conductive Polymer Nanocomposite for Intelligent Pesticide Sensing: Trends, Challenges, and Future Prospects.Molecules (Basel, Switzerland) · 2026Review
- Recent Progress in Artificial Intelligence in Biosensor Development: From Bioprobe Design to Fabrication and Signal Analysis.Biosensors · 2026Review
- High-throughput Optical Analysis to Inform Design of Electrochemical Biosensors.ACS measurement science au · 2026Review
- Electrochemical liquid biopsy across cancer care pathway.The journal of liquid biopsy · 2026Review
- Integrating Metabolomics and Machine Learning for Advanced Chemical Detection.Sensors (Basel, Switzerland) · 2026Review
- Recent Proceedings of Advanced Electrochemiluminescence Imaging Technology and Applications in Accurate Analysis.Chemical & biomedical imaging · 2026Review
- A Novel System for Physiological Signal Monitoring and Health-Informed Electrotactile Feedback for First Responders.Sensors (Basel, Switzerland) · 2026Article
- Machine Learning for Neurotransmitter Monitoring by Fast Voltammetry: Current and Future Prospects.ACS chemical neuroscience · 2026Review
- Artificial Intelligence-Based Wearable Sensing Technologies for the Management of Cancer, Diabetes, and COVID-19.Biosensors · 2025Review
- Noninvasive and Sensitive Biosensor for the Detection of Oral Cancer Prognostic Biomarkers.Small (Weinheim an der Bergstrasse, Germany) · 2025Article
- Classifying metal passivity from EIS using interpretable machine learning with minimal data.Scientific reports · 2025Article
- Article
- Carbon nanomaterials as smart interfaces in ultrathin films for high-performance electrochemical sensors: a critical review.RSC advances · 2025Review
- Machine-Learning-Aided Advanced Electrochemical Biosensors.Advanced materials (Deerfield Beach, Fla.) · 2025Review
- AI-Empowered Electrochemical Sensors for Biomedical Applications: Technological Advances and Future Challenges.Biosensors · 2025Review
- Machine learning-assisted point-of-care diagnostics for cardiovascular healthcare.Bioengineering & translational medicine · 2025Review
- Bioelectroanalytical Technologies for Advancing the Frontiers To Democratize Personalized Desired Health.Analytical chemistry · 2025Review
- Artificial intelligence enhanced electrochemical immunoassay for staphylococcal enterotoxin B.Scientific reports · 2025Article
- Enhancing pH prediction accuracy in AlScientific reports · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
The so-coined fourth paradigm in science has reached the sensing area, with the use of machine learning (ML) toward data-driven improvements in sensitivity, reproducibility, and accuracy, along with the determination of multiple targets from a single measurement using multi-output regression models. Particularly, the use of supervised ML models trained on large data sets produced by electrical and electrochemical bio/sensors has emerged as an impacting trend in the literature by allowing accurate analyses even in the presence of usual issues such as electrode fouling, poor signal-to-noise ratio, chemical interferences, and matrix effects. In this trend article, apart from an outlook for the coming years, we present examples from the literature that demonstrate how helpful ML algorithms can be for dispensing the adoption of experimental methods to address the aforesaid interfering issues, ultimately contributing to translate testing technologies into on-site, practical, and daily applications.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.