医学诊断的多模式融合方面:全面审查
Sachin Kumar1, Sita Rani2, Shivani Sharma3
1Akian College of Science and Engineering, American University of Armenia, Yerevan 0019, Armenia.
Bioengineering (Basel, Switzerland)
|January 8, 2025
概括
多模式医疗诊断,整合来自不同来源的数据,提高诊断准确性和效率. 本综述探讨了推进人工智能驱动医疗保健的多式联络方法,挑战和伦理考虑.
科学领域:
- 医疗信息学 医疗信息学
- 医疗保健中的人工智能
- 诊断医学 诊断医学
背景情况:
- 医学诊断传统上依赖于单个数据源,这可能是限制性的.
- 由于医疗专家的短缺,对自动诊断工具的需求越来越大.
- 多模式数据融合为更精确,更有信心的诊断提供了一个有前途的途径.
研究的目的:
- 提供多式联络医疗诊断的全面审查.
- 为研究人员和学者提供有关多式联网数据方面和挑战的知识.
- 讨论多式联运信息的需要和自动诊断中的潜在解决方案.
主要方法:
- 系统审查来自知名期刊和出版商的高质量文章.
- 在医学诊断中分析多式联络数据融合技术.
- 检查人工智能驱动的医学诊断中的挑战和伦理考虑.
主要成果:
- 结合来自多个医疗来源的信息,大大提高了诊断的信心.
- 使用多式联接技术进行自动诊断,随着人工智能的发展,越来越有可能实现.
- 确定了多式联运数据集成的关键挑战,并提出了潜在的解决方案.
结论:
- 多模式医疗诊断对于提高诊断准确性和患者护理至关重要.
- 需要进一步的研究来解决人工智能在诊断中的复杂性和伦理影响.
- 本综述是促进多式联络医学研究的基础资源.
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