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Designing Chinese hospital emergency departments to leverage artificial intelligence-a systematic literature review on the challenges and opportunities.
Tan, Sijie; Mills, Grant.
Affiliation
  • Tan S; Bartlett School of Sustainable Construction, Bartlett Faculty of the Built Environment, University College London, London, United Kingdom.
  • Mills G; Bartlett School of Sustainable Construction, Bartlett Faculty of the Built Environment, University College London, London, United Kingdom.
Front Med Technol ; 6: 1307625, 2024.
Article in En | MEDLINE | ID: mdl-38577009
ABSTRACT
Artificial intelligence (AI) has witnessed rapid advances in the healthcare domain in recent years, especially in the emergency field, where AI is likely to radically reshape medical service delivery. Although AI has substantial potential to enhance diagnostic accuracy and operational efficiency in hospitals, research on its applications in Emergency Department building design remains relatively scarce. Therefore, this study aims to investigate Emergency Department facility design by identifying the challenges and opportunities of using AI. Two systematic literature reviews are combined, one in AI and the other in sensors, to explore their potential application to support decision-making, resource optimisation and patient monitoring. These reviews have then informed a discussion on integrating AI sensors in contemporary Emergency Department designs for use in China to support the evidence base on resuscitation units, emergency operating rooms and Emergency Department Intensive Care Unit (ED-ICU) design. We hope to inform the strategic implementation of AI sensors and how they might transform Emergency Department design to support medical staff and enhance the patient experience.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Front Med Technol Year: 2024 Document type: Article Affiliation country: Reino Unido Country of publication: Suiza

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Front Med Technol Year: 2024 Document type: Article Affiliation country: Reino Unido Country of publication: Suiza