将光学和电学传感与机器学习相结合,实现先进的颗粒表征。

IF 3 4区 医学 Q3 ENGINEERING, BIOMEDICAL
Mahtab Kokabi, Muhammad Tayyab, Gulam M. Rather, Arastou Pournadali Khamseh, Daniel Cheng, Edward P. DeMauro, Mehdi Javanmard
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引用次数: 0

摘要

粒子分类在各种科学和技术应用中发挥着至关重要的作用,例如在医疗保健应用中区分细菌和病毒,或对癌细胞进行识别和分类。这项技术需要对粒子特性进行准确有效的分析。在本研究中,我们研究了通过多模态方法整合电学和光学特征进行颗粒分类的方法。我们应用机器学习分类器算法来评估将这些测量方法结合在一起所产生的影响。我们的结果表明,多模态方法优于独立分析电学或光学特征。通过整合两种模式,我们获得了 94.9% 的平均测试准确率,而单独分析电学特征的准确率为 66.4%,单独分析光学特征的准确率为 90.7%。这凸显了电学和光学信息的互补性及其提高分类性能的潜力。通过利用电学传感和光学成像技术,我们的多模态方法可以更深入地了解粒子特性,并提供对复杂生物系统更全面的理解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Integrating optical and electrical sensing with machine learning for advanced particle characterization

Integrating optical and electrical sensing with machine learning for advanced particle characterization

Particle classification plays a crucial role in various scientific and technological applications, such as differentiating between bacteria and viruses in healthcare applications or identifying and classifying cancer cells. This technique requires accurate and efficient analysis of particle properties. In this study, we investigated the integration of electrical and optical features through a multimodal approach for particle classification. Machine learning classifier algorithms were applied to evaluate the impact of combining these measurements. Our results demonstrate the superiority of the multimodal approach over analyzing electrical or optical features independently. We achieved an average test accuracy of 94.9% by integrating both modalities, compared to 66.4% for electrical features alone and 90.7% for optical features alone. This highlights the complementary nature of electrical and optical information and its potential for enhancing classification performance. By leveraging electrical sensing and optical imaging techniques, our multimodal approach provides deeper insights into particle properties and offers a more comprehensive understanding of complex biological systems.

Graphical abstract

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来源期刊
Biomedical Microdevices
Biomedical Microdevices 工程技术-工程:生物医学
CiteScore
6.90
自引率
3.60%
发文量
32
审稿时长
6 months
期刊介绍: Biomedical Microdevices: BioMEMS and Biomedical Nanotechnology is an interdisciplinary periodical devoted to all aspects of research in the medical diagnostic and therapeutic applications of Micro-Electro-Mechanical Systems (BioMEMS) and nanotechnology for medicine and biology. General subjects of interest include the design, characterization, testing, modeling and clinical validation of microfabricated systems, and their integration on-chip and in larger functional units. The specific interests of the Journal include systems for neural stimulation and recording, bioseparation technologies such as nanofilters and electrophoretic equipment, miniaturized analytic and DNA identification systems, biosensors, and micro/nanotechnologies for cell and tissue research, tissue engineering, cell transplantation, and the controlled release of drugs and biological molecules. Contributions reporting on fundamental and applied investigations of the material science, biochemistry, and physics of biomedical microdevices and nanotechnology are encouraged. A non-exhaustive list of fields of interest includes: nanoparticle synthesis, characterization, and validation of therapeutic or imaging efficacy in animal models; biocompatibility; biochemical modification of microfabricated devices, with reference to non-specific protein adsorption, and the active immobilization and patterning of proteins on micro/nanofabricated surfaces; the dynamics of fluids in micro-and-nano-fabricated channels; the electromechanical and structural response of micro/nanofabricated systems; the interactions of microdevices with cells and tissues, including biocompatibility and biodegradation studies; variations in the characteristics of the systems as a function of the micro/nanofabrication parameters.
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