Jove
Visualize
联系我们
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

相关概念视频

Diabetic Retinopathy01:27

Diabetic Retinopathy

DefinitionDiabetic retinopathy is a microvascular complication of diabetes affecting the retinal blood vessels.Risk FactorsDiabetic retinopathy is present in almost all individuals with type 1 diabetes and more than 60% of those with type 2 diabetes after two decades of disease.The risk increases with poor glycemic control, hypertension, dyslipidemia, smoking, pregnancy, and puberty.Although cataracts and glaucoma are also more frequent in people with diabetes, retinopathy remains the leading...

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

Spatially-resolved single-cell imaging of melanoma brain metastases identifies localized immune patterns predictive of immune checkpoint blockade response.

Neuro-oncology·2026
Same author

Rerouting Eye Care: How AI and Telemedicine Are Reshaping Ophthalmology Patient Journeys in the United Kingdom and Germany.

Journal of medical Internet research·2026
Same author

VectorSage: enhancing PubMed article retrieval with advanced semantic search.

Bioinformatics advances·2026
Same author

The cost of dual-task walking: Cognitive demands restrict gaze behaviour and gait planning.

PloS one·2026
Same author

Potential Causes of Shedding Aggregations in Prairie Rattlesnakes.

Ecology and evolution·2026
Same author

Unraveling the complexity of skin's biological aging utilizing epigenetic clocks.

Clinical epigenetics·2026

相关实验视频

Updated: May 19, 2026

Behavioral Assessment of Visual Function via Optomotor Response and Cognitive Function via Y-Maze in Diabetic Rats
07:41

Behavioral Assessment of Visual Function via Optomotor Response and Cognitive Function via Y-Maze in Diabetic Rats

Published on: October 23, 2020

6.7K

用现实数据定制基于人工智能的查:糖尿病视网膜病变的实际见解

Broder Poschkamp1, Liane Kantz2,3, Petra Augstein2

  • 1Department of Ophthalmology, University Medicine Greifswald, Greifswald, Germany.

Acta ophthalmologica
|September 11, 2025
PubMed
概括

现实世界的人工智能 (AI) 对糖尿病视网膜病变 (DR) 的查显示性能低于预期,但定制提高了准确性. 人工智能工具显著减少了糖尿病护理中眼科医生评估的需要.

关键词:
人工智能调整调整优登指数是什么意思人工智能的人工智能是人工智能.糖尿病视网膜病变 糖尿病视网膜病变非米德里亚图像成像技术现实世界的真实世界.

更多相关视频

Author Spotlight: Understanding Retinal Vessel Resilience and Disease Progression
04:36

Author Spotlight: Understanding Retinal Vessel Resilience and Disease Progression

Published on: January 12, 2024

1.6K
Tear-Derived Exosomal miR-15a as New Diagnostic Tool for Diabetic Retinopathy
07:45

Tear-Derived Exosomal miR-15a as New Diagnostic Tool for Diabetic Retinopathy

Published on: December 30, 2025

245

相关实验视频

Last Updated: May 19, 2026

Behavioral Assessment of Visual Function via Optomotor Response and Cognitive Function via Y-Maze in Diabetic Rats
07:41

Behavioral Assessment of Visual Function via Optomotor Response and Cognitive Function via Y-Maze in Diabetic Rats

Published on: October 23, 2020

6.7K
Author Spotlight: Understanding Retinal Vessel Resilience and Disease Progression
04:36

Author Spotlight: Understanding Retinal Vessel Resilience and Disease Progression

Published on: January 12, 2024

1.6K
Tear-Derived Exosomal miR-15a as New Diagnostic Tool for Diabetic Retinopathy
07:45

Tear-Derived Exosomal miR-15a as New Diagnostic Tool for Diabetic Retinopathy

Published on: December 30, 2025

245

科学领域:

  • 眼科医生 眼科 眼科
  • 医疗成像医学成像
  • 人工智能的人工智能

背景情况:

  • 糖尿病视网膜病变 (DR) 是全球糖尿病成年人视力损失的主要原因.
  • 现有的AI选工具 (IDx-DR,RetCAD) 在受控环境中显示出高灵敏度.
  • 现实世界DR查面临着图像质量和当地医疗保健适应方面的挑战.

研究的目的:

  • 为了比较AI算法 (IDx-DR,RetCAD) 进行非肌底性肌底性查与眼科医生肌底性脑膜镜.
  • 评估定制推门修改 ("格里夫斯瓦尔德修改") 对AI查结果的影响.
  • 评估AI性能,考虑图像质量和患者在现实环境中的包容性.

主要方法:

  • 一项一中心观察性研究包括1716名糖尿病患者.
  • 评估了灵敏度,特异性,不可分类的图像比例,并减少了眼科评估.
  • 使用基于回归的AI算法Youden指数定制的推门.

主要成果:

  • 观察到高率的不可分类图像 (5.7%未获取,2.1%不完整的IDx-DR).
  • 人工智能查减少了眼科检查需求的47.5%至78.5%.
  • 灵敏度各不相同:可分析图像的70.4% (RetCAD) 到93.6% (RetCAD与格里夫斯瓦尔德修饰);包括所有患者在内的52.7% (IDx-DR) 到79.9% (RetCAD与格里夫斯瓦尔德修饰).

结论:

  • 在现实世界中,AI DR查性能可能低于在包括非可分析患者时的受控研究.
  • 回归AI算法允许推门定制,提高选准确度.
  • 人工智能查有效地减少了糖尿病护理中DR评估的临床负担.