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

Issues And Trends In Healthcare Delivery System01:29

Issues And Trends In Healthcare Delivery System

6.3K
The issues and trends in healthcare delivery are constantly changing. The COVID-19 pandemic is one recent issue that wreaked havoc on healthcare systems, causing a shortage of healthcare workers, high demand for medicines and supplies, and increased medical expenditure due to a lack of insurance. Other issues include rising healthcare costs and care fragmentation.
Cost Containment
Payment for healthcare services has historically promoted adoption of costly and often unnecessary or inefficient...
6.3K

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

Toward autonomous robotic-assisted and microrobotic surgery.

Science advances·2026
Same author

Therapy Driven Protocol: Early Ambulation for Lower Extremity Grafts.

Journal of burn care & research : official publication of the American Burn Association·2026
Same author

Verification Status, Rehabilitation Staffing, and Care Practices in U.S Outpatient Burn Clinics.

Journal of burn care & research : official publication of the American Burn Association·2026
Same author

Depression and its associated factors among adult women in Bangladesh during the July 2024 revolution.

Discover mental health·2026
Same author

The Diabetic Foot Consortium Biomarker Platform Study: A New Approach to Advance Diabetic Foot Ulcer Healing.

Advances in wound care·2026
Same author

Amendment to Atractylenolide I enhances responsiveness to immune checkpoint blockade therapy by activating tumor antigen presentation.

The Journal of clinical investigation·2026

相关实验视频

Updated: Feb 20, 2026

Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System
05:33

Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System

Published on: July 11, 2025

1.2K

使用人工智能为医疗保健提供自动化非侵入性烧伤诊断系统:AMBUSH-AI

Mohamed El Masry1,2, Md Masudur Rahman3,4, Surya C Gnyawali1,2

  • 1Department of Surgery, School of Medicine, University of Pittsburgh, Pittsburgh, PA, 15219.

Annals of surgery
|February 19, 2026
PubMed
概括

人工智能 (AI) 与超声波成像相结合,可以准确预测燃烧深度. 这项新技术在识别三度烧伤方面具有很高的准确性,提高了烧伤护理的诊断能力.

关键词:
人工智能烧伤诊断诊断在 GPT 中,GPT 必须是 GPT.在TDI超声波中,预测燃烧深度的预测深度学习是一种深度学习.可以解释性的解释性.进行外科手术的决策.视觉语言模型的模型.

更多相关视频

Author Spotlight: AI-Driven Trypanosome Species Detection from Microscopic Images
08:20

Author Spotlight: AI-Driven Trypanosome Species Detection from Microscopic Images

Published on: October 27, 2023

2.7K
Detection and Isolation of Cancer in Prostate Biopsies Using Stimulated Raman Histology and Artificial Intelligence
08:05

Detection and Isolation of Cancer in Prostate Biopsies Using Stimulated Raman Histology and Artificial Intelligence

Published on: June 10, 2025

1.3K

相关实验视频

Last Updated: Feb 20, 2026

Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System
05:33

Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System

Published on: July 11, 2025

1.2K
Author Spotlight: AI-Driven Trypanosome Species Detection from Microscopic Images
08:20

Author Spotlight: AI-Driven Trypanosome Species Detection from Microscopic Images

Published on: October 27, 2023

2.7K
Detection and Isolation of Cancer in Prostate Biopsies Using Stimulated Raman Histology and Artificial Intelligence
08:05

Detection and Isolation of Cancer in Prostate Biopsies Using Stimulated Raman Histology and Artificial Intelligence

Published on: June 10, 2025

1.3K

科学领域:

  • 医疗技术 医疗技术 医学技术
  • 人工智能的人工智能
  • 超声波成像 超声波成像

背景情况:

  • 准确的烧伤深度评估对于外科决定至关重要.
  • 目前用于区分深部部分厚度和三度烧伤的诊断准确性有限 (76%为专家,50%为非专家).
  • 这种局限性凸显了在烧伤管理中需要改进的诊断工具的需要.

研究的目的:

  • 开发和评估一种人工智能驱动的技术,用于预测烧伤深度.
  • 将FDA批准的超声波方式与AI集成,以提高诊断准确度.
  • 为了克服区分烧伤深度的诊断挑战.

主要方法:

  • 使用猪烧模型开发了一个AI框架,并在人类实验中进行了测试.
  • 获得了组织多普勒弹性成像 (TDI) 和波B模式超声波图像.
  • 人工智能解释了TDI和B模式图像,在某些情况下使用活检作为基本真相.

主要成果:

  • 人工智能算法在识别猪的三度烧伤时实现了100%的准确性.
  • 在人体受试者中,人工智能方法在识别三度烧伤时表现出95%的准确性.
  • 人工智能模型分析了TDI和B模式超声波图像,以预测燃烧深度.

结论:

  • 人工智能对B模式超声波和TDI图像的解释是一个可行的策略.
  • 这种方法显著提高了预测烧伤深度的诊断准确性.
  • 开发的技术有望改善烧伤评估和治疗规划.