Literature DB >> 36026569

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

Samaneh Zare Harofte1, Madjid Soltani1,2,3,4,5, Saeed Siavashy1, Kaamran Raahemifar6,7,8.   

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.
© 2022 Wiley-VCH GmbH.

Entities:  

Keywords:  artificial intelligence-on-a-chip; deep learning; lab-on-a-chip; machine learning; microfluidics

Mesh:

Year:  2022        PMID: 36026569     DOI: 10.1002/smll.202203169

Source DB:  PubMed          Journal:  Small        ISSN: 1613-6810            Impact factor:   15.153


  1 in total

1.  Artificial Intelligence in Public Health: Current Trends and Future Possibilities.

Authors:  Daniele Giansanti
Journal:  Int J Environ Res Public Health       Date:  2022-09-21       Impact factor: 4.614

  1 in total

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