人工智能在冷保存中的应用:技术进步和未来的挑战
Xingyue Lei1, Liqun He2, Gang Zhao1
1Department of Electronic Engineering and Information Science, University of Science and Technology of China, Hefei, 230027, Anhui, China.
Cryobiology
|February 5, 2026
概括
人工智能 (AI) 通过优化协议,预测损伤和改善细胞,胚胎和组织的质量控制来增强冷保存. 人工智能在冷保存中的这种应用提高了生存率和效率.
科学领域:
- 生物技术是生物技术.
- 计算生物学 计算生物学
- 低温生物学 低温生物学
背景情况:
- 冷保存对于保存细胞,胚胎和组织等生物样本至关重要.
- 目前的冷保存方法在效率,损害控制和生存率方面面临挑战.
- 人工智能 (AI) 为这些挑战提供了潜在的解决方案.
研究的目的:
- 系统地审查人工智能在冷保存方面的研究进展和应用状态.
- 分析人工智能的机制,优势和挑战,以提高冷保存效率和样品可行性.
- 在冷保存技术中确定人工智能发展的未来方向.
主要方法:
- 对冷保存中人工智能应用的最新研究进行系统审查.
- 分析AI在协议优化,损害预测和质量控制中的作用.
- 检查人工智能对冷保护剂配方,过程控制和稳定性监测的影响.
主要成果:
- 人工智能在提高冷保存效率,减少生物样本损伤和增加复苏后生存率方面具有显著的优势.
- 关键应用包括人工智能驱动的冷保护剂 (CPA) 配方设计,优化结/解过程以及增强的长期稳定性监测.
- 人工智能有助于跨度建模,动态流程优化和样本状态的预测.
结论:
- 人工智能是促进冷保存的变革性技术,为生物样本的保存提供了更好的结果.
- 未来的发展应侧重于多模式数据融合,增强人工智能可解释性,以及用于更广泛的临床和工业应用的智能自适应控制系统.
- 本次审查为冷保存技术的智能发展提供了基础.
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