Towards optimal design of patient isolation units in emergency rooms to prevent airborne virus transmission: From computational fluid dynamics to data-driven modeling

• Published in: Computers in biology and medicine Vol. 173; p. 108309
• Main Authors: Lee, Jong Hyeon, Shim, Jae Woo, Lim, Min Hyuk, Baek, Changhoon, Jeon, Byoungjun, Cho, Minwoo, Park, Sungwoo, Choi, Dong Hyun, Kim, Byeong Soo, Yoon, Dan, Kim, Young Gyun, Cho, Seung Yeon, Lee, Kyung-Min, Yeo, Myoung-Souk, Zo, Hangman, Shin, Sang Do, Kim, Sungwan
• Format: Journal Article
• Language: English
• Published: United States Elsevier Ltd 01.05.2024; Elsevier Limited
• Subjects: Air flow; Airborne virus; Computational fluid dynamics; Computer applications; Computer Simulation; COVID-19; Data-driven machine-learning-based modeling; Design optimization; Emergency medical care; Emergency medical services; Emergency Service, Hospital; Humans; Hydrodynamics; Infection Control - methods; Infectious diseases; Internal Medicine; Isolation units; Machine learning; Mathematical models; Other; Pandemics; Parameter identification; Patient Isolation; Patient isolation unit; Simulation; Ventilation; COVID-19; Patient isolation unit; Computational fluid dynamics; Data-driven machine-learning-based modeling; Airborne virus

Patient isolation units (PIUs) can be an effective method for effective infection control. Computational fluid dynamics (CFD) is commonly used for PIU design; however, optimizing this design requires extensive computational resources. Our study aims to provide data-driven models to determine the PIU...