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Issues And Trends In Healthcare Delivery System01:29

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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.
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German physicist Wilhelm Röntgen (1845–1923) was experimenting with electrical current when he discovered that a mysterious and invisible "ray" would pass through his flesh but leave an outline of his bones on a screen coated with a metal compound. In 1895, Röntgen made the first durable record of the internal parts of a living human: an "X-ray" image (as it came to be called) of his wife’s hand. Scientists worldwide quickly began their own experiments with...
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Tomography refers to imaging by sections. Computed tomography (CT) is a non-invasive imaging technique that uses computers to analyze several cross-sectional X-rays to reveal minute details about structures in the body.
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Magnetic resonance imaging (MRI) is a noninvasive medical imaging technique based on a phenomenon of nuclear physics discovered in the 1930s, in which matter exposed to magnetic fields and radio waves was found to emit radio signals. In 1970, a physician and researcher named Raymond Damadian noticed that malignant (cancerous) tissue gave off different signals than normal body tissue. He applied for a patent for the first MRI scanning device in clinical use by the early 1980s. The early MRI...
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通过人工智能彻底改变放射学.

Abhiyan Bhandari1

  • 1General Medicine, Wexham Park Hospital, Slough, GBR.

Cureus
|October 30, 2024
PubMed
概括

人工智能 (AI) 通过提高诊断准确性和工作流程效率来增强放射学. 解决透明度和偏见等挑战是实现AI在患者护理中的全部潜力的关键.

科学领域:

  • 放射学 放射学是指放射学
  • 医疗成像医学成像
  • 人工智能的人工智能

背景情况:

  • 人工智能 (AI) 正在越来越多地影响医疗保健,特别是在医学成像方面.
  • 人工智能在放射学领域的诊断准确性,工作流效率和患者护理方面提供了潜在的进步.

研究的目的:

  • 探索人工智能对放射学各个子领域的影响.
  • 强调AI在改善临床实践和患者治疗结果方面的潜力.

主要方法:

  • 审查人工智能驱动的技术,包括机器学习,深度学习和自然语言处理 (NLP).
  • 对放射学中的AI应用进行分析,例如用于图像分析和异常检测的计算机辅助诊断 (CAD).
  • 整合来自多种成像模式 (CT,MRI,PET) 的数据,以获得全面的见解.

主要成果:

  • 人工智能工具在分析医疗图像和检测瘤等异常方面表现出高精度.
  • 人工智能促进了个性化治疗规划,并补充了现有的放射科医生工作流程.
  • 人工智能自动化日常任务,有助于早期发现疾病,并支持临床决策.

结论:

  • 人工智能通过增强诊断能力和简化工作流程来彻底改变放射学具有重大前景.
关键词:
人工智能的人工智能是人工智能.诊断 诊断 诊断 诊断 诊断 诊断患者护理 患者护理放射学 放射学是指放射学工作流的优化工作流的优化.

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  • 为了有效地整合人工智能,必须解决算法透明度,数据隐私和偏见缓解等挑战.
  • 利益相关者之间的合作和强有力的道德准则对于在临床实践中安全有效地实施人工智能至关重要.