生物过程
自动汇总
斯科普斯
生物炼制
人工智能
计算机科学
过程(计算)
领域(数学)
领域(数学分析)
机器学习
生化工程
工程类
数学
化学
梅德林
生物化学
生物燃料
操作系统
数学分析
化学工程
纯数学
废物管理
作者
Chao‐Tung Yang,Endah Kristiani,Yoong Kit Leong,Jo‐Shu Chang
标识
DOI:10.1016/j.biortech.2023.128625
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.
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