Search research articles

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 Journal Methods Collections JoVE Encyclopedia of Experiments 存档

教育

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual 教师资源中心教师网站

使用条款与条件

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

Three-Dimensional Metamaterial for Plasmon-Enhanced Raman Scattering at any Excitation Wavelengths from the Visible to Near-Infrared Range.

Analytical chemistry·2020

Same author

Correction to: Predicting and clustering plant CLE genes with a new method developed specifically for short amino acid sequences.

BMC genomics·2020

Same author

Transferrin receptor (TFRC) is essential for meiotic progression during mouse spermatogenesis.

Zygote (Cambridge, England)·2020

Same author

Effect of aspartic acid on the crystallization kinetics of ACP and dentin remineralization.

Journal of the mechanical behavior of biomedical materials·2020

Same author

Model vs. observation discrepancy in aerosol characteristics during a half-year long campaign in Northeast China: The role of biomass burning.

Environmental pollution (Barking, Essex : 1987)·2020

Same author

Multiple Transformations among Anion-based A<sub>2</sub>L<sub>3</sub> Assemblies: Bicapped Trigonal Antiprism A<sub>8</sub>L<sub>12</sub>, Tetrahedron A<sub>4</sub>L<sub>6</sub>, and Triple Helicate A<sub>2</sub>L<sub>3</sub> (A = Anion).

Journal of the American Chemical Society·2020

Search research articles

相关实验视频

Updated: Jul 7, 2025

Assessing Early Stage Open-Angle Glaucoma in Patients by Isolated-Check Visual Evoked Potential

Assessing Early Stage Open-Angle Glaucoma in Patients by Isolated-Check Visual Evoked Potential

Published on: May 25, 2020

使用EfficientNet对基于人工智能的近视性白症分级方法的研究.

Bo Zheng^1,2, Maotao Zhang¹, Shaojun Zhu^1,2

¹School of Information Engineering, Huzhou University, Huzhou, China.

Indian journal of ophthalmology

|December 22, 2023

概括

使用EfficientNet的人工智能模型准确地从 fundus 图像中对近视性黄斑症进行评分. 这种AI工具有助于眼科医生早期诊断近视性黄斑病的各个阶段.

更多相关视频

Author Spotlight: An Automated Method for Assessing Visual Acuity in Infants and Toddlers Using an Eye-Tracking System

Author Spotlight: An Automated Method for Assessing Visual Acuity in Infants and Toddlers Using an Eye-Tracking System

Published on: March 17, 2023

Binocular Dynamic Visual Acuity in Eyeglass-Corrected Myopic Patients

Binocular Dynamic Visual Acuity in Eyeglass-Corrected Myopic Patients

Published on: March 29, 2022

相关实验视频

Last Updated: Jul 7, 2025

Assessing Early Stage Open-Angle Glaucoma in Patients by Isolated-Check Visual Evoked Potential

Assessing Early Stage Open-Angle Glaucoma in Patients by Isolated-Check Visual Evoked Potential

Published on: May 25, 2020

Author Spotlight: An Automated Method for Assessing Visual Acuity in Infants and Toddlers Using an Eye-Tracking System

Author Spotlight: An Automated Method for Assessing Visual Acuity in Infants and Toddlers Using an Eye-Tracking System

Published on: March 17, 2023

Binocular Dynamic Visual Acuity in Eyeglass-Corrected Myopic Patients

Binocular Dynamic Visual Acuity in Eyeglass-Corrected Myopic Patients

Published on: March 29, 2022

科学领域:

眼科医生眼科眼科
人工智能的人工智能
医疗成像医学成像

背景情况:

近视性黄斑病的分级对于及时干预至关重要.
当前的分级方法可能是主观的,耗时的.
迟迟诊断近视性黄斑病症可能导致视力受损.

研究的目的:

使用EfficientNet.Net开发一种基于人工智能的近视性黄斑病的评分系统.
为了提高诊断不同程度近视性黄斑病的效率和准确性.
为了克服近视性黄斑病的当前诊断工作流程的局限性.

主要方法:

在4642张彩色基底照片上训练了EfficientNet模型 (B0-B7).
将EfficientNet模型与VGG16和ResNet50进行了比较.
评估模型使用灵敏度,特异性,F1得分,AUC,kappa值和精度.

主要成果:

EfficientNet-B0模型实现了最高的卡帕值 (88.32%) 和精度 (83.58%).
观察到高灵敏度用于诊断形底部 (96.86%) 和黄斑缩 (88.75%).
所有条件的特异性都超过了93%,AUC达到0.992的形底部.

结论:

EfficientNet模型可以有效地从 fundus 图像中对近视性黄斑病进行分级.
人工智能模型可以区分健康的底部和四度近视性黄斑病.
这种人工智能工具有潜力帮助眼科医生初步诊断近视性黄斑病.