整合Omics数据和AI用于癌症诊断和预后
Yousaku Ozaki1, Phil Broughton1, Hamed Abdollahi2
1Department of Biomedical Sciences, University of South Carolina School of Medicine Greenville, Greenville, SC 29605, USA.
Cancers
|July 13, 2024
概括
人工智能 (AI) 通过分析各种患者数据来帮助癌症诊断和预后. 进一步的研究对于安全的临床整合和改善结果至关重要.
科学领域:
- 在瘤学瘤学.
- 医疗信息学 医疗信息学
- 人工智能的人工智能
背景情况:
- 癌症仍然是导致死亡的主要原因,强调需要准确及及时的诊断和预后.
- 人工智能 (AI) 为组织和分析复杂的患者数据提供了强大的能力,以改善癌症护理.
- 人工智能在瘤学的临床实用性正在迅速发展,需要对最近的进展进行全面审查.
研究的目的:
- 审查人工智能 (AI) 在癌症诊断和预后中的多样化应用.
- 评估AI工具的临床实用性,利用瘤学中的各种数据类型.
- 综合近期关于人工智能在癌症护理方面的研究结果.
主要方法:
- 在PubMed和EBSCO数据库上对2020年1月1日至2023年12月22日的出版物进行了系统的文献搜索.
- 关键搜索术语包括"人工智能"和"机器学习"以确定相关研究.
- 包括89项研究,按数据类型 (多组,放射,病态,临床,实验室) 和重点 (诊断,预后) 分类.
主要成果:
- 在癌症诊断和预后方面的AI应用在89项研究中进行了分析,按数据模式分类.
- 研究使用了多种omics数据 (基因组学,转录组学,表观组学,蛋白质组学),放射组学,病理组学以及临床/实验室数据.
- 八项研究整合了多种omics数据类型,突出了人工智能多模式数据分析的潜力.
结论:
- 将人工智能与奥米克和临床数据集成,代表了癌症诊断和预后的重大进步.
- 人工智能显示出极大的潜力,可以提高癌症护理的准确性和效率.
- 正在进行的前性研究对于改善AI算法解释性和确保安全的临床整合以造福患者至关重要.
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