Artificial Intelligence and Machine Learning in Emergency Medicine

• Autorzy: Tang Kenneth Jian Wei , Ang Candice Ke En , Constantinides Theodoros , Rajinikanth V. , Acharya U. Rajendra , Cheong Kang Hao

Identyfikatory

DOI

10.1016/j.bbe.2020.12.002

• Języki publikacji: EN

Abstrakty

EN

The advent of Artificial Intelligence (AI) has resulted in development of novel applications in a multitude of fields, such as in Medicine, to aid medical professionals in clinical diagnosis. Specifically, the field of Emergency Medicine has been of immense interest to researchers, with vast untapped potential for AI solutions to improve operational efficiencies and quality of healthcare. Aside from primary healthcare facilities, the Emergency Department serves as the first line of contact to patients, who often present with varying and undifferentiated symptoms. Several challenges faced by clinicians and patients alike, such as waiting times and diagnostic dilemmas, present opportunities for application of AI solutions. In this paper, we aim to summarise the applications of AI in the field of Emergency Medicine by reviewing recent developments in Emergency Department operations and in the clinical management of patients.

Słowa kluczowe

EN

emergency medicine; emergency department; artificial intelligence; machine learning; deep learning

PL

ratownictwo medyczne; oddział ratunkowy; sztuczna inteligencja; uczenie maszynowe; uczenie głębokie

• Wydawca: Nałęcz Institute of Biocybernetics and Biomedical Engineering of the Polish Academy of Sciences ; Elsevier
• Czasopismo: Biocybernetics and Biomedical Engineering
• Rocznik: 2021
• Tom: Vol. 41, no. 1
• Strony: 156--172
• Opis fizyczny: Bibliogr. 99 poz., rys., tab.

Twórcy

autor

Tang Kenneth Jian Wei

• Science, Mathematics and Technology Cluster, Singapore University of Technology and Design, 8 Somapah Rd, S487372, Singapore

autor

Ang Candice Ke En

• MOH Holdings Pte Ltd, 1 Maritime Square, S099253, Singapore

autor

Constantinides Theodoros

• University of Bristol, Queen's Building, Bristol BS8 1TR, UK

autor

Rajinikanth V.

• Department of Electronics and Instrumentation Engineering, St. Joseph's College of Engineering, Chennai 600119, India

autor

Acharya U. Rajendra

• Department of Electronics and Computer Engineering, Ngee Ann Polytechnic, Singapore; Department of Biomedical Informatics and Medical Engineering, Asia University, Taichung, Taiwan; International Research Organization for Advanced Science and Technology (IROAST), Kumamoto University, Kumamoto, Japan

autor

Cheong Kang Hao

• Science, Mathematics and Technology Cluster, Singapore University of Technology and Design, 8 Somapah Rd, S487372, Singapore

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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).