ReviewFrontiers in chemistry2024
Advances in machine learning-enhanced nanozymes.
Review in Frontiers in chemistry, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 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
10 citing papers in PubMed.
- Artificial intelligence-guided nanozyme engineering for chronic wound healing: from rational design to precision therapeutics.Bioactive materials · 2027Review
- Colorimetric detection of amino acids enabled by functional nanomaterials: mechanisms, performance evaluation, and translational perspectives.Mikrochimica acta · 2026Review
- Optical Waveguide Lightmode Spectroscopy: A Versatile Technique for Real-Time, Label-Free Biosensing.Sensors (Basel, Switzerland) · 2026Review
- Endocrine nanozymology: Nanozyme applications in diabetes, obesity, and hormonal disorders.Theranostics · 2026Review
- Nanozyme-Based Anti-Inflammatory Strategies in Cardiovascular Disease Management: Clinical Prospects and Challenges.International journal of nanomedicine · 2026Review
- Catalysis Beyond Enzymes: Ceria Nanozyme as a Smart Platform for Biocatalysis, Anti-oxidant Defense, and Biosensing.Topics in current chemistry (Cham) · 2025Review
- Graphene-based nanozymes for revolutionizing biomedical research.RSC advances · 2025Review
- Deep Learning-Enhanced Nanozyme-Based Biosensors for Next-Generation Medical Diagnostics.Biosensors · 2025Review
- An Amperometric Enzyme-Nanozyme Biosensor for Glucose Detection.Biosensors · 2025Article
- Nanomedicine in cardiovascular and cerebrovascular diseases: targeted nanozyme therapies and their clinical potential and current challenges.Journal of nanobiotechnology · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Nanozymes, synthetic nanomaterials that mimic the catalytic functions of natural enzymes, have emerged as transformative technologies for biosensing, diagnostics, and environmental monitoring. Since their introduction, nanozymes have rapidly evolved with significant advancements in their design and applications, particularly through the integration of machine learning (ML). Machine learning (ML) has optimized nanozyme efficiency by predicting ideal size, shape, and surface chemistry, reducing experimental time and resources. This review explores the rapid advancements in nanozyme technology, highlighting the role of ML in improving performance across various bioapplications, including real-time monitoring and the development of chemiluminescent, electrochemical and colorimetric sensors. We discuss the evolution of different types of nanozymes, their catalytic mechanisms, and the impact of ML on their property optimization. Furthermore, this review addresses challenges related to data quality, scalability, and standardization, while highlighting future directions for ML-driven nanozyme development. By examining recent innovations, this review highlights the potential of combining nanozymes with ML to drive the development of next-generation diagnostic and detection technologies.
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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.