ArticleIEEE International Conference on Nano/Micro Engineered and Molecular Systems. IEEE International Conference on Nano/Micro Engineered and Molecular Systems2022
Aluminum Oxide-Coated Particle Differentiation Employing Supervised Machine Learning and Impedance Cytometry.
Article in IEEE International Conference on Nano/Micro Engineered and Molecular Systems. IEEE International Conference on Nano/Micro Engineered and Molecular Systems, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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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.
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Who cites it
2 citing papers in PubMed.
- Multi-modal sensing with integrated machine learning to differentiate specific leukocytes targeted by electrically sensitive hybrid particles.Biosensors & bioelectronics · 2023Article
- Nucleic Acid Quantification by Multi-Frequency Impedance Cytometry and Machine Learning.Biosensors · 2023Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
This article uses a supervised machine learning (ML) system for identifying groups of nanoparticles coated with metal oxides of varying thicknesses using a microfluidic impedance cytometer. These particles generate unique impedance signatures when probed with a multifrequency electric field and finds applications in enabling many multiplexed biosensing technologies. However, current experimental and data processing techniques are unable to sensitively differentiate different metal oxide coated particle types. Here, we employ various machine learning models and collect multiple particle metrics measured. In reported experiments, a 75% accuracy was determined to separate aluminum oxide coated (10nm and 30nm), which is significantly greater than observing only univariate data between different microparticle types. This approach will enable ML models to differentiate such particles with greater accuracies.
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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.