人工智能,大数据和免疫力监管:挑战和机遇
Bhagirath Singh1,2,3, Anthony M Jevnikar1,4, Eric Desjardins3,5
1Department of Microbiology and Immunology, University of Western Ontario, London, ON, Canada.
Archivum immunologiae et therapiae experimentalis
|February 29, 2024
概括
人工智能 (AI) 和大数据 (BD) 分析通过分析复杂的免疫相互作用,为了解和治疗免疫疾病提供了新的策略. 伦理准则对于将这些人工智能驱动的见解应用于基于免疫的干预和维持健康至关重要.
科学领域:
- 免疫学 免疫学 免疫学
- 生物信息学是一种生物信息学.
- 计算生物学 计算生物学
背景情况:
- 免疫系统的调节涉及复杂的遗传,分子和细胞相互作用.
- 奥米克技术产生了大量的大数据 (BD) 用于研究免疫力.
- 人工智能 (AI) 提供了理论和临床免疫学的突破潜力.
研究的目的:
- 探索AI在分析免疫学大数据中的应用.
- 确定免疫疾病的新研究途径和治疗策略.
- 解决在免疫学中使用人工智能的道德和监管挑战.
主要方法:
- 通过使用人工智能工具的omics技术生成的大型数据集的分析.
- 基于大数据分析的可测试假设的制定.
- 对免疫学研究中人工智能的伦理和监管考虑的审查.
主要成果:
- 人工智能驱动的免疫性BD分析可以导致疾病治疗和预防的创新策略.
- 人工智能可以帮助诊断罕见疾病和管理自身免疫性疾病,过敏和癌症等疾病.
- 复杂的免疫相互作用,通常是传统方法无法处理的,可以通过AI分析来解决.
结论:
- 人工智能和BD分析对推动基础免疫学和临床应用具有重大前景.
- 制定伦理和监管框架对于指导AI驱动的基于免疫的干预措施至关重要.
- 需要立即关注,为在免疫学大数据分析中负责任地使用AI制定准则.
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