Big data and machine learning driven bioprocessing – Recent trends and critical analysis

Chao Tung Yang, Endah Kristiani, Yoong Kit Leong, Jo Shu Chang

研究成果: Article同行評審

12 引文 斯高帕斯(Scopus)

摘要

Given the potential of machine learning algorithms in revolutionizing the bioengineering field, this paper examined and summarized the literature related to artificial intelligence (AI) in the bioprocessing field. Natural language processing (NLP) was employed to explore the direction of the research domain. All the papers from 2013 to 2022 with specific keywords of bioprocessing using AI were extracted from Scopus and grouped into two five-year periods of 2013-to-2017 and 2018-to-2022, where the past and recent research directions were compared. Based on this procedure, selected sample papers from recent five years were subjected to further review and analysis. The result shows that 50% of the publications in the past five-year focused on topics related to hybrid models, ANN, biopharmaceutical manufacturing, and biorefinery. The summarization and analysis of the outcome indicated that implementing AI could improve the design and process engineering strategies in bioprocessing fields.

原文English
文章編號128625
期刊Bioresource technology
372
DOIs
出版狀態Published - 2023 3月

All Science Journal Classification (ASJC) codes

  • 生物工程
  • 環境工程
  • 可再生能源、永續發展與環境
  • 廢物管理和處置

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