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人工智能在用于诊断和治疗的芯片实验室中的最新进展

Recent Advances of Utilizing Artificial Intelligence in Lab on a Chip for Diagnosis and Treatment.

作者信息

Zare Harofte Samaneh, Soltani Madjid, Siavashy Saeed, Raahemifar Kaamran

机构信息

Department of Mechanical Engineering, K. N. Toosi University of Technology, Tehran, 19967-15433, Iran.

Department of Electrical and Computer Engineering, Faculty of Engineering, University of Waterloo, Waterloo, ON, N2L 3G1, Canada.

出版信息

Small. 2022 Oct;18(42):e2203169. doi: 10.1002/smll.202203169. Epub 2022 Aug 26.

Abstract

Nowadays, artificial intelligence (AI) creates numerous promising opportunities in the life sciences. AI methods can be significantly advantageous for analyzing the massive datasets provided by biotechnology systems for biological and biomedical applications. Microfluidics, with the developments in controlled reaction chambers, high-throughput arrays, and positioning systems, generate big data that is not necessarily analyzed successfully. Integrating AI and microfluidics can pave the way for both experimental and analytical throughputs in biotechnology research. Microfluidics enhances the experimental methods and reduces the cost and scale, while AI methods significantly improve the analysis of huge datasets obtained from high-throughput and multiplexed microfluidics. This review briefly presents a survey of the role of AI and microfluidics in biotechnology. Also, the incorporation of AI with microfluidics is comprehensively investigated. Specifically, recent studies that perform flow cytometry cell classification, cell isolation, and a combination of them by gaining from both AI methods and microfluidic techniques are covered. Despite all current challenges, various fields of biotechnology can be remarkably affected by the combination of AI and microfluidic technologies. Some of these fields include point-of-care systems, precision, personalized medicine, regenerative medicine, prognostics, diagnostics, and treatment of oncology and non-oncology-related diseases.

摘要

如今,人工智能(AI)在生命科学领域创造了众多充满前景的机会。对于分析生物技术系统为生物和生物医学应用提供的海量数据集而言,人工智能方法具有显著优势。随着可控反应室、高通量阵列和定位系统的发展,微流控技术产生了不一定能被成功分析的大数据。将人工智能与微流控技术相结合可为生物技术研究中的实验通量和分析通量铺平道路。微流控技术改进了实验方法,降低了成本和规模,而人工智能方法则显著提升了对从高通量和多重微流控技术获得的海量数据集的分析能力。本综述简要介绍了人工智能和微流控技术在生物技术中的作用。此外,还全面研究了人工智能与微流控技术的结合。具体而言,涵盖了近期通过利用人工智能方法和微流控技术进行流式细胞术细胞分类、细胞分离以及二者结合的研究。尽管存在当前所有挑战,但人工智能和微流控技术的结合仍可对生物技术的各个领域产生显著影响。其中一些领域包括即时护理系统、精准医学、个性化医疗、再生医学、肿瘤学和非肿瘤学相关疾病的预后、诊断及治疗。

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