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AI for Manufacturing and Healthcare: a chemistry and engineering perspective

Authors :
Chen, Jihua
Yuan, Yue
Ziabari, Amir Koushyar
Xu, Xuan
Zhang, Honghai
Christakopoulos, Panagiotis
Bonnesen, Peter V.
Ivanov, Ilia N.
Ganesh, Panchapakesan
Wang, Chen
Jaimes, Karen Patino
Yang, Guang
Kumar, Rajeev
Sumpter, Bobby G.
Advincula, Rigoberto
Publication Year :
2024

Abstract

Artificial Intelligence (AI) approaches are increasingly being applied to more and more domains of Science, Engineering, Chemistry, and Industries to not only improve efficiencies and enhance productivity, but also enable new capabilities. The new opportunities range from automated molecule design and screening, properties prediction, gaining insights of chemical reactions, to computer-aided design, predictive maintenance of systems, robotics, and autonomous vehicles. This review focuses on the new applications of AI in manufacturing and healthcare. For the Manufacturing Industries, we focus on AI and algorithms for (1) Battery, (2) Flow Chemistry, (3) Additive Manufacturing, (4) Sensors, and (5) Machine Vision. For Healthcare applications, we focus on: (1) Medical Vision (2) Diagnosis, (3) Protein Design, and (4) Drug Discovery. In the end, related topics are discussed, including physics integrated machine learning, model explainability, security, and governance during model deployment.

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2405.01520
Document Type :
Working Paper