在癌症中研究和应用omics和人工智能
Ye Zhang1, Wenwen Ma1, Zhiqiang Huang1
1School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, People's Republic of China.
Physics in medicine and biology
|July 30, 2024
概括
人工智能 (AI) 和多omics数据分析正在彻底改变癌症研究. 这种整合为个性化癌症治疗和改善患者治疗结果提供了新的视角.
科学领域:
- 瘤学和生物信息学
- 计算生物学和基因组学
背景情况:
- 由于癌症的发病率和死亡率很高,癌症对全球健康构成重大威胁.
- 高通量技术的进步已经产生了大量不同的癌症基因组学数据 (例如,基因组学,表观基因组学,转录基因组学,蛋白质基因组学,代谢基因组学).
- 整合这些庞大的多omics数据集对理解瘤发育提出了重大挑战.
研究的目的:
- 近年来引入先进的多领域数据分析技术.
- 介绍在癌症研究中将多omics数据与人工智能 (AI) 结合在一起的优势.
- 讨论在瘤学中的多学科分析和人工智能的挑战和未来前景.
主要方法:
- 综述和综合最近在多omics数据分析技术的进展.
- 探索人工智能和机器学习应用程序,以分析综合癌症多omics数据.
- 人工智能和多omics集成在癌症研究中的案例研究介绍.
主要成果:
- 人工智能技术,特别是机器学习,正在成为分析复杂多omics数据的强大工具.
- 多omics数据和AI的整合有助于优化癌症查,诊断和治疗策略.
- 智能医疗,包括人工智能驱动的预后分析和个性化治疗,正在获得突出地位.
结论:
- 多学科数据和人工智能之间的协同作用为推进瘤学研究提供了巨大的潜力.
- 这种综合方法为个性化癌症治疗策略提供了新的途径.
- 解决当前在多学科分析和人工智能的挑战对于实现个性化瘤学的全部潜力至关重要.
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