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Issues And Trends In Healthcare Delivery System01:29

Issues And Trends In Healthcare Delivery System

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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...
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Updated: Sep 17, 2025

Author Spotlight: Advancing CBCT and Digital Dental Image Integration with AI-Assisted Digitization
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Author Spotlight: Advancing CBCT and Digital Dental Image Integration with AI-Assisted Digitization

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基于成像的手术部位感染检测使用人工智能

Hala Muaddi1, Ashok Choudhary2, Frank Lee1

  • 1Division of Hepatobiliary and Pancreas Surgery, Mayo Clinic, Rochester, MN.

Annals of surgery
|July 3, 2025
PubMed
概括
此摘要是机器生成的。

一个人工智能管道有效地评估患者提交的伤口图像,以检测手术部位感染 (SSI). 这种人工智能工具有助于早期检测,减少临床医生的工作量并改善术后护理结果.

关键词:
人工智能是一种人工智能.手术后的监测 术后的监测手术部位感染 手术部位感染

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科学领域:

  • 医疗人工智能 医疗人工智能
  • 数字健康数字健康
  • 手术部位感染检测检测

背景情况:

  • 越来越多的门诊手术和远程监控给临床医生带来了重要的行政任务.
  • 早期发现手术部位感染 (SSIs) 对于尽量减少术后并发症至关重要.
  • 患者通过在线门户网站提交的伤口图像变得越来越普遍.

研究的目的:

  • 创建基于人工智能 (AI) 的系统来评估和优先考虑患者提交的术后伤口图像.
  • 为了自动评估伤口图像并检测潜在的手术部位感染 (SSIs).

主要方法:

  • 开发了一种两级AI模型,用于切口检测和在术后伤口图像中检测SSI.
  • 利用了来自梅奥诊所医院 (2019-2022) 6060 个患者图像的数据集,包括来自国家外科质量改善计划 (NSQIP) 的SSI结果.
  • 通过交叉验证,数据增强和图像质量评估,包括跨种族群体的敏感性分析,评估了四个预训练的架构.

主要成果:

  • 视觉变压器模型在切口检测 (0.94) 和SSI检测 (0.73) 中实现了高精度.
  • 人工智能管道在图像质量评估方面表现强.
  • 在不同种族小组中,表现一致,表明有效性公平.

结论:

  • 开发的AI管道显示了自动评估术后伤口图像的巨大潜力.
  • 这项技术可以有效地帮助早期检测手术部位感染 (SSI).
  • 人工智能系统有望减少临床医生的工作量,并提高术后患者护理的质量.