ReviewPrecision chemistry2024
Single-Molecule Bioelectronic Sensors with AI-Aided Data Analysis: Convergence and Challenges.
Review in Precision chemistry, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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
8 citing papers in PubMed.
- ResNet-KAN for Small-Sample Chemical Formulation Prediction: Hybrid Architecture and Interpretability Analysis.Precision chemistry · 2026Article
- Photonic biosensors based on nanoparticle superstructures: from data analysis to artificial intelligence (AI) detection.Fundamental research · 2026Review
- Fingerprint Recognition Based on Molecular-Scale Conductance Response via Electrochemically Gated Quantum Tunnelling.Sensors (Basel, Switzerland) · 2026Article
- Performance improvement of single-molecule sensors through deep learning-based decoding of tunneling signals enables sub-attomolar sensitivity.Nature communications · 2026Article
- Review
- Advanced Materials for Biological Field-Effect Transistors (Bio-FETs) in Precision Healthcare and Biosensing.Advanced healthcare materials · 2025Review
- Bioelectronic Therapeutics: A Revolutionary Medical Practice in Health Care.Bioelectricity · 2025Review
- Artificial-Intelligence Driven Precision Chemistry.Precision chemistry · 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
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Single-molecule bioelectronic sensing, a groundbreaking domain in biological research, has revolutionized our understanding of molecules by revealing deep insights into fundamental biological processes. The advent of emergent technologies, such as nanogapped electrodes and nanopores, has greatly enhanced this field, providing exceptional sensitivity, resolution, and integration capabilities. However, challenges persist, such as complex data sets with high noise levels and stochastic molecular dynamics. Artificial intelligence (AI) has stepped in to address these issues with its powerful data processing capabilities. AI algorithms effectively extract meaningful features, detect subtle changes, improve signal-to-noise ratios, and uncover hidden patterns in massive data. This review explores the synergy between AI and single-molecule bioelectronic sensing, focusing on how AI enhances signal processing and data analysis to boost accuracy and reliability. We also discuss current limitations and future directions for integrating AI, highlighting its potential to advance biological research and technological innovation.
Identifiers
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.