当前位置: X-MOL 学术Annu. Rev. Anal. Chem. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
AI in Measurement Science
Annual Review of Analytical Chemistry ( IF 5.9 ) Pub Date : 2021-07-27 , DOI: 10.1146/annurev-anchem-091520-091450
Chao Liu 1, 2 , Jiashu Sun 1, 2
Affiliation  

Measurement of biological systems containing biomolecules and bioparticles is a key task in the fields of analytical chemistry, biology, and medicine. Driven by the complex nature of biological systems and unprecedented amounts of measurement data, artificial intelligence (AI) in measurement science has rapidly advanced from the use of silicon-based machine learning (ML) for data mining to the development of molecular computing with improved sensitivity and accuracy. This review presents an overview of fundamental ML methodologies and discusses their applications in disease diagnostics, biomarker discovery, and imaging analysis. We next provide the working principles of molecular computing using logic gates and arithmetical devices, which can be employed for in situ detection, computation, and signal transduction for biological systems. This review concludes by summarizing the strengths and limitations of AI-involved biological measurement in fundamental and applied research.

中文翻译:


测量科学中的人工智能

测量包含生物分子和生物颗粒的生物系统是分析化学、生物学和医学领域的一项关键任务。在生物系统的复杂性和前所未有的测量数据量的推动下,测量科学中的人工智能 (AI) 从使用基于硅的机器学习 (ML) 进行数据挖掘迅速发展到具有更高灵敏度的分子计算的发展和准确性。本综述概述了基本 ML 方法,并讨论了它们在疾病诊断、生物标志物发现和成像分析中的应用。我们接下来提供了使用逻辑门和算术设备进行分子计算的工作原理,可用于生物系统的原位检测、计算和信号转导。

更新日期:2021-07-28
down
wechat
bug