Machine-Learning-Assisted Nanozyme-Based Sensor Arrays: Construction, Empowerment, and Applications Article Swipe
Jinjin Liu
,
Xinyu Chen
,
Qiaoqiao Diao
,
Zheng Tang
,
Xiangheng Niu
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.3390/bios15060344
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.3390/bios15060344
In the past decade, nanozymes have been attracting increasing interest in academia due to their stable performance, low cost, and easy modification. With the catalytic signal amplification feature, nanozymes not only find wide use in traditional “lock-and-key” single-target detection but hold great potential in high-throughput multiobjective analysis via fabricating sensor arrays. In particular, the rise of machine learning in recent years has greatly advanced the design, construction, signal processing, and utilization of sensor arrays. The constructive collaboration of nanozymes, sensor arrays, and machine learning is accelerating the development of biochemical sensors. To highlight the emerging field, in this minireview, we created a concise summary of machine-learning-assisted nanozyme-based sensor arrays. First, the construction of nanozyme-involved sensor arrays is introduced from several aspects, including nanozyme materials and activities, sensing variables, and signal outputs. Then, the roles of machine learning in signal treatment, information extraction, and outcome feedback are emphasized. Afterwards, typical applications of machine-learning-assisted nanozyme-involved sensor arrays in environmental detection, food analysis, and biomedical sensing are discussed. Finally, the promise of machine-learning-assisted nanozyme-based sensor arrays in biochemical sensing is highlighted, and some future trends are also pointed out to attract more interest and effort to promote the emerging field for better practical use.
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Metadata
- Type
- review
- Language
- en
- Landing Page
- https://doi.org/10.3390/bios15060344
- OA Status
- gold
- Cited By
- 3
- References
- 93
- Related Works
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- OpenAlex ID
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All OpenAlex metadata
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https://openalex.org/W4410858799Canonical identifier for this work in OpenAlex
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https://doi.org/10.3390/bios15060344Digital Object Identifier
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Machine-Learning-Assisted Nanozyme-Based Sensor Arrays: Construction, Empowerment, and ApplicationsWork title
- Type
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reviewOpenAlex work type
- Language
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enPrimary language
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2025Year of publication
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2025-05-29Full publication date if available
- Authors
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Jinjin Liu, Xinyu Chen, Qiaoqiao Diao, Zheng Tang, Xiangheng NiuList of authors in order
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https://doi.org/10.3390/bios15060344Publisher landing page
- Open access
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YesWhether a free full text is available
- OA status
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goldOpen access status per OpenAlex
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https://doi.org/10.3390/bios15060344Direct OA link when available
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Empowerment, Computer science, Nanotechnology, Materials science, Political science, LawTop concepts (fields/topics) attached by OpenAlex
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3Total citation count in OpenAlex
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2025: 3Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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