通过多式联运数据融合推进医疗保健:对技术和应用进行全面审查
Jing Ru Teoh1, Jian Dong2, Xiaowei Zuo3
1Department of Biomedical Engineering, University of Malaya, Kuala Lumpur, Malaysia.
PeerJ. Computer science
|December 9, 2024
概括
本综述探讨了医疗保健中的多式联络数据融合,整合了医疗图像和电子健康记录等多元数据,以改进人工智能驱动的诊断和治疗规划.
科学领域:
- 生物医学信息学 生物医学信息学
- 人工智能在医学中的应用
- 数据科学数据科学数据科学
背景情况:
- 医疗保健产生各种数据 (图像,电子健康记录),需要有效的整合.
- 多模式数据融合在医疗保健中至关重要,但目前有限.
- 需要对最近的进展进行全面的审查.
研究的目的:
- 审查有关医疗保健 (2018-2024) 中多式联运数据融合的现有文献.
- 专注于整合各种医疗数据类型以进行增强分析的方法.
- 突出人工智能驱动医疗保健中的挑战,好处和应用.
主要方法:
- 对69篇作品 (2018-2024) 的系统文献综述.
- 融合技术的分析:早期,中期和晚期的融合.
- 整合策略的分类:图像-文本,多图像等.
主要成果:
- 确定了将医疗图像与结构化/非结构化数据集成的关键方法.
- 详细介绍了各种融合方法 (早期,中期,晚期) 和它们的应用.
- 突出了数据异质性,标准化和可解释性方面的挑战.
结论:
- 多式联网数据融合在推进医学诊断和治疗规划方面具有重大潜力.
- 需要进一步的研究来克服目前的局限性,并充分利用综合医疗数据.
- 这一审查为开发更强大的医疗保健人工智能模型提供了基础.
关键词:
面临的挑战 挑战决策 决策是做出决定的.欧洲人权理事会 欧洲人权理事会早期的核聚变 早期的核聚变医疗保健 医疗保健 医疗保健 医疗保健中间核聚变的中间核聚变晚期核聚变是什么意思医学图像 医学图像 医学图像多式联运数据融合技术患者护理 患者护理更多相关视频
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