Jove
Visualize
联系我们

相关概念视频

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Acoustofluidic Focusing for High-Throughput and Sensitive Analysis of Shape-Encoded Hydrogel Microparticles in Multiplex Immunoassay.

ACS sensors·2026
Same author

Amplification-Free and Label-Free Multiplexed Profiling of Extracellular Vesicle-Derived MicroRNA via Micropore Sensing Based on PNA-Functionalized Hydrogel Barcodes.

ACS sensors·2026
Same author

Nouveau benzo-mimetics of 17R-Resolvin D2 are potent resolution agonists for inflammation.

iScience·2026
Same author

MIDAS: rapid, multiplexed molecular profiling for integrated host-pathogen analysis.

Nature communications·2025
Same author

Temperature-Responsive, Injectable Poly(organophosphazene)-Based Hydrogel Adhesive for One-Step Hemostasis and Wound Closure.

Biomacromolecules·2025
Same author

Oxygen-free discontinuous dewetting in a degassed mold for anisotropic colloidal hydrogel microparticle synthesis.

Lab on a chip·2025
Same journal

Robust and Sensitive Electrochemical Biosensor Based on Cascade Interface Engineering for piRNA Detection in Breast Cancer Diagnosis.

ACS sensors·2026
Same journal

CRISPR-Cas-Based Platform for Single-Step Quantification of Monoclonal Antibodies at Point-of-Care.

ACS sensors·2026
Same journal

Engineering Guide RNAs for CRISPR-Based Biosensors.

ACS sensors·2026
Same journal

Multimodal Detection of Low Water Contents in Ethanol Using a Plasmon-Berreman-Enhanced Metasurface Infrared Absorber.

ACS sensors·2026
Same journal

3D-Printed Hollow Microneedle Potentiometric Sensors: A Modular Approach.

ACS sensors·2026
Same journal

A Genetically Encoded Fluorescent Sensor for Protein Arginine Phosphorylation.

ACS sensors·2026
查看所有相关文章
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关实验视频

Updated: Jul 21, 2025

Fragmenting Bulk Hydrogels and Processing into Granular Hydrogels for Biomedical Applications
10:18

Fragmenting Bulk Hydrogels and Processing into Granular Hydrogels for Biomedical Applications

Published on: May 17, 2022

5.7K

对图形编码的水凝微粒进行高度灵活的基于深度学习的自动分析.

Jun Hee Choi1, Wookyoung Jang1, Yong Jun Lim1

  • 1Department of Chemical and Biological Engineering, Korea University, Seoul 02841, South Korea.

ACS sensors
|July 25, 2023
PubMed
概括
此摘要是机器生成的。

这项研究引入了一种高效的深度学习方法,用于分析基于水凝微粒 (HMP) 的生物测试. 自动注释和合成数据混合显著提高了多重诊断的分析速度和准确性.

关键词:
自动注释 - 自动注释深度学习是一种深度学习.图形编码图形编码水凝微粒的微粒是什么多重免疫测试多重免疫测试综合数据 综合数据

更多相关视频

Preparation and Characterization of Graphene-Based 3D Biohybrid Hydrogel Bioink for Peripheral Neuroengineering
10:17

Preparation and Characterization of Graphene-Based 3D Biohybrid Hydrogel Bioink for Peripheral Neuroengineering

Published on: May 16, 2022

2.3K
Microfluidic Synthesis of Microgel Building Blocks for Microporous Annealed Particle Scaffold
09:34

Microfluidic Synthesis of Microgel Building Blocks for Microporous Annealed Particle Scaffold

Published on: June 16, 2022

3.2K

相关实验视频

Last Updated: Jul 21, 2025

Fragmenting Bulk Hydrogels and Processing into Granular Hydrogels for Biomedical Applications
10:18

Fragmenting Bulk Hydrogels and Processing into Granular Hydrogels for Biomedical Applications

Published on: May 17, 2022

5.7K
Preparation and Characterization of Graphene-Based 3D Biohybrid Hydrogel Bioink for Peripheral Neuroengineering
10:17

Preparation and Characterization of Graphene-Based 3D Biohybrid Hydrogel Bioink for Peripheral Neuroengineering

Published on: May 16, 2022

2.3K
Microfluidic Synthesis of Microgel Building Blocks for Microporous Annealed Particle Scaffold
09:34

Microfluidic Synthesis of Microgel Building Blocks for Microporous Annealed Particle Scaffold

Published on: June 16, 2022

3.2K

科学领域:

  • 生物医学工程 生物医学工程
  • 纳米技术 纳米技术
  • 人工智能的人工智能

背景情况:

  • 基于凝微粒 (HMP) 的生物测试提供了高多重检测能力,灵敏度和特异性.
  • 深度学习增强了HMP分析,但手动注释和普通粒子数据限制了功能纳米材料的准确性.
  • 现有的手动数据注释是劳动密集型和耗时的.

研究的目的:

  • 开发一种高效的基于深度学习的分析,用于用各种图形代码和功能纳米材料编码的HMP.
  • 在HMP分析中克服手动数据注释和普通粒子数据的局限性.
  • 提高HMP生物试验数据处理的速度和准确性.

主要方法:

  • 使用自动注释来快速准备数据集,实现0.11秒/图像吞吐量.
  • 采用合成数据混合用于模型培训,用磁纳米粒子增强HMP分析.
  • 开发了一个深度学习模型来分析各种图形代码和功能纳米材料.

主要成果:

  • 使用合成数据混合实现了0.88的平均精度,比标准方法提高了两倍.
  • 经过三重免疫试验的实践应用证明了产前的生物标志物.
  • 在分析结果图像时,每个样本的处理吞吐量达到0.353秒.

结论:

  • 提出的自动注释和合成数据混合策略显著提高了基于深度学习的HMP生物测试分析的效率和准确性.
  • 这种自动化方法解决了手动注释和普通粒子数据的局限性,使复杂的HMP能够进行可靠的分析.
  • 这种方法显示出快速可靠的诊断应用的强大潜力,如先兆子生物标志物试验所证明的那样.