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Artificial Intelligence and Machine Learning in Emergency Medicine

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

Biocybernetics and Biomedical Engineering

2021

Vol. 41, no. 1

156--172

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.

A method of prioritizing victims of a mass casualty event for managing medical rescue operations

Tomczyk Ł., Kulesza Z.

Control and Cybernetics

2016

Vol. 45, no. 3

355--370

The paper discusses the concept of ICT-aided identiﬁcation of mass casualty events and prioritization of victims of a mass casualty event for treatment in a Hospital Emergency Department (HED), which relies on a distributed network-centric Data Communications System for Managing Medical Rescue Operations (DCSMMRO). A method for triaging patients is presented and the functional architecture of a utility application for setting treatment priorities in DCSMMRO is designed. The proposed method and the developed application for the data communications system were veriﬁed on the example of a hypothetical event.