深度学习增强的基于纳米酶的生物传感器,用于下一代医学诊断
Seungah Lee1, Nayra A M Moussa2, Seong Ho Kang1,2
1Department of Applied Chemistry and Institute of Natural Sciences, Kyung Hee University, Yongin-si 17104, Gyeonggi-do, Republic of Korea.
Biosensors
|September 26, 2025
概括
深度学习 (DL) 增强了纳米酶生物传感器,用于先进的医学诊断. 这种整合改善了疾病检测,成像和护理点检测,为精确医疗保健铺平了道路.
科学领域:
- 生物医学工程 生物医学工程
- 人工智能的人工智能
- 纳米技术纳米技术
背景情况:
- 基于纳米酶的生物传感器提供了有前途的诊断能力.
- 深度学习 (DL) 提供了增强纳米酶性能和应用的机会.
- 下一代医疗诊断需要创新的传感策略.
研究的目的:
- 审查深度学习 (DL) 与基于纳米酶的生物传感的整合.
- 探索DL如何增强纳米酶设计,优化和预测建模.
- 讨论人工智能增强的纳米酶诊断中的应用,挑战和未来方向.
主要方法:
- 关于DL架构和纳米酶催化物的文献综述.
- 分析DL在阐明催化机制 (例如双原子位点) 中的作用.
- 检查DL在生物标志物检测,医学成像和临床诊断中的应用.
主要成果:
- DL改善了纳米酶设计,功能优化和预测建模.
- 关键应用包括疾病生物标志物检测和增强的医学成像.
- 可穿戴生物传感器和智能平台利用DL进行实时分析和决策.
结论:
- 纳米酶和DL的融合为智能生物传感提供了显著的潜力.
- 挑战包括数据标准化,模型稳定性和临床翻译.
- 未来的方向包括与IoMT的整合,个性化医疗和可持续发展.
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