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

Mouse Models of Cancer Study02:43

Mouse Models of Cancer Study

Mice have long served as models for studying human biology and pathology because of their phylogenetic and physiological similarity with humans. They are also easy to maintain and breed in the laboratory, and hence, many inbred strains are now available for research. Studies on mice have contributed immeasurably to our understanding of cancer biology.
The development of transgenic, knockout, and knock-in mice has led to an exponential increase in their use as model organisms in research,...
Mouse Models of Cancer Study02:43

Mouse Models of Cancer Study

Mice have long served as models for studying human biology and pathology because of their phylogenetic and physiological similarity with humans. They are also easy to maintain and breed in the laboratory, and hence, many inbred strains are now available for research. Studies on mice have contributed immeasurably to our understanding of cancer biology.
The development of transgenic, knockout, and knock-in mice has led to an exponential increase in their use as model organisms in research,...

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

Kidney Segmentation of Histopathological Images with Edge-Aware U-Net to Support Medical Diagnosis and Treatment Planning.

Bioengineering (Basel, Switzerland)·2026
Same author

Uncertainty-Aware Framework for CT Radiation Dose Optimization in the Active Surveillance of Small Renal Masses: Clinical and Radiological Considerations.

Diagnostics (Basel, Switzerland)·2026
Same author

FibroidX: Vision Transformer-Powered Prognosis and Recurrence Prediction for Uterine Fibroids Using Ultrasound Images.

Cancers·2026
Same author

Prompt-Driven Multimodal Segmentation with Dynamic Fusion for Adaptive and Robust Medical Imaging with Applications to Cancer Diagnosis.

Cancers·2025
Same author

Cloud-based real-time enhancement for disease prediction using Confluent Cloud, Apache Kafka, feature optimization, and explainable artificial intelligence.

PeerJ. Computer science·2025
Same author

Transformative Approaches in Breast Cancer Detection: Integrating Transformers into Computer-Aided Diagnosis for Histopathological Classification.

Bioengineering (Basel, Switzerland)·2025

相关实验视频

Updated: Jun 21, 2026

A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images
04:23

A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images

Published on: April 21, 2023

1.8K

ViT-PSO-SVM:基于将视觉变压器与粒子群优化和支持向量机器集成的宫癌预测.

Abdulaziz AlMohimeed1, Mohamed Shehata2, Nora El-Rashidy3

  • 1College of Computer and Information Sciences, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh 13318, Saudi Arabia.

Bioengineering (Basel, Switzerland)
|July 27, 2024
PubMed
概括

这项研究引入了一种新型的人工智能模型,即带有粒子群优化和支持矢量机 (ViT-PSO-SVM) 的视觉转换器,用于准确,非侵入性的宫癌检测. 人工智能方法显著改善了早期诊断,潜在地提高了全球患者的治疗结果.

关键词:
这就是ViT-PSO-SVM.宫癌:子宫癌是一种癌症.诊断模型 诊断模型 诊断模型

更多相关视频

Author Spotlight: Insights into Visual Cortex Research Through Wide-View fMRI Mapping
07:11

Author Spotlight: Insights into Visual Cortex Research Through Wide-View fMRI Mapping

Published on: December 8, 2023

1.4K
Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines
08:27

Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines

Published on: January 5, 2024

1.0K

相关实验视频

Last Updated: Jun 21, 2026

A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images
04:23

A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images

Published on: April 21, 2023

1.8K
Author Spotlight: Insights into Visual Cortex Research Through Wide-View fMRI Mapping
07:11

Author Spotlight: Insights into Visual Cortex Research Through Wide-View fMRI Mapping

Published on: December 8, 2023

1.4K
Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines
08:27

Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines

Published on: January 5, 2024

1.0K

科学领域:

  • 在瘤学瘤学.
  • 医疗成像医学成像
  • 人工智能的人工智能

背景情况:

  • 宫癌 (CCa) 是全球女性癌症死亡的主要原因,需要改进早期检测方法.
  • 目前的诊断标准,如活检,是侵入性的;高精度的非侵入性成像是非常理想的.
  • 人工智能 (AI),特别是视觉转换器 (ViT),显示出医学图像分析的潜力,与传统方法相竞争.

研究的目的:

  • 评估视觉变压器 (ViT) 的有效性,以从细胞图像中预测宫癌.
  • 开发和评估一种新的混合AI模型,ViT-PSO-SVM,用于增强宫癌诊断.
  • 展示AI作为可靠,非侵入性工具的潜力,以改善宫癌检测和患者的治疗结果.

主要方法:

  • 使用视觉变压器 (ViT) 从宫细胞图像数据集 (SipakMed和Herlev) 提取特征.
  • 使用粒子群优化 (PSO) 优化提取的特征,以减少复杂性和改进表示.
  • 使用与ViT-PSO框架集成的支持矢量机 (SVM) 模型对宫癌的分类.
  • 通过使用准确度和F1分数指标,对两,三和五类分类场景中的模型性能进行评估.
  • 应用GradCAM用于可解释AI (XAI) 来可视化对预测至关重要的图像区域.

主要成果:

  • 拟议的ViT-PSO-SVM方法在SipakMed数据集 (两类) 上实现了高精度 (99.112%) 和F1得分 (99.113%).
  • 该模型在Herlev数据集上表现出强的表现,达到97.778%的准确性和97.805%的F1得分 (两类).
  • 在宫癌分类任务中,ViT-PSO-SVM模型的表现优于现有的ViT,CNN和预训练模型.
  • GradCAM可视化提供了对模型决策过程的见解,证实了它专注于相关的图像特征.

结论:

  • 开发的ViT-PSO-SVM方法是一个可行的和有效的AI工具,用于准确检测宫癌.
  • 这种人工智能驱动的方法为传统诊断程序提供了一个有希望的非侵入性替代方案.
  • 该模型的高性能和可解释性表明它有可能显著改善宫癌患者的全球医疗保健结果.