Unmanned aerial vehicle based intelligent triage system in mass-casualty incidents using 5G and artificial intelligence

Lu, Jianxiong

doi:10.5847/wjem.j.1920-8642.2023.066

Cited by 8 publications

(2 citation statements)

References 37 publications

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“…They developed an intelligent triage system based on two AI algorithms, namely OpenPose and YOLO. They concluded that the proposed technique may provide an alternative technique for the triage of MCIs, and it is an innovative method in emergency rescue 31 …”

Section: Discussionmentioning

confidence: 99%

Emergency medical services preparedness in mass casualty incidents: A qualitative study

Saadatmand,

Ahmadi Marzaleh,

Abbasi

et al. 2023

Health Science Reports

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Background and AimsThe effective response of emergency medical services in mass casualty incidents (MCIs) calls for sufficient preparation. The components of preparation must be determined first to achieve this goal. This study aimed to describe the elements of preparedness of emergency medical services for MCIs.MethodsA qualitative study was carried out on emergency medical service systems in Iran (from April 2022 to mid‐March 2023), using in‐depth semistructured interviews with participants who were managers and members of the incident command team, experts, technicians, paramedics, and telecommunicators of emergency medical services. Interviews were carried out face‐to‐face and via telephone. The data were collected using voice recorder and transcript and analyzed by content analysis method. This study was conducted using the consolidated criteria for reporting qualitative research.ResultsThirty‐six participants were included in the study. A total of 834 codes were analyzed. Thirteen components were extracted from the study and classified as five categories including “Strengthening management and organization,” “individual and group empowerment,” “capacity expansion,” “technology and infrastructure development,” and “operational response measures.”ConclusionEmergency medical service preparedness in response to MCIs is a critical issue. For improving preparedness, the main components must be identified. The study results described the elements of emergency medical service preparedness, which could be used as a framework for developing the national model of emergency medical service preparedness in MCIs.

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Section: Discussionmentioning

confidence: 99%

Emergency medical services preparedness in mass casualty incidents: A qualitative study

Saadatmand,

Ahmadi Marzaleh,

Abbasi

et al. 2023

Health Science Reports

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“…Although 'Search & Rescue' is not explicitly 'Health Care Delivery', it was featured as a topic within healthcare delivery manuscripts. These topics relate to autonomous control systems, GPS, and smart detection devices, presumably improving search operations in diverse environments and situations [39,43,44]. This research aimed to develop techniques that enable UAVs to locate and assist patients swiftly and accurately, often in challenging or hazardous terrain.…”

Section: Drones In the Delivery Of Time-critical Medical Itemsmentioning

confidence: 99%

Emerging Research Topics in Drone Healthcare Delivery

Campbell,

Bosiocic,

Hvala

et al. 2024

Drones

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The application of drones to assist with healthcare delivery has grown rapidly over the last decade. This industry is supported by a growing research field, and we have undertaken a systematic review of the published literature. Web-based searches returned 290 relevant manuscripts published between 2010 and 2024. We applied Topic Modelling to this corpus of literature, which examines word association and connectedness within the research papers. The modelling identified two emerging research themes with little connection between them: those who used drones to deliver time-critical medical items and those who used drones to deliver non-time-critical medical items. The former was in response to medical emergencies, while the latter was for enhancing resilience in the healthcare supply chain. The topics within these research themes exhibited notable differences. The delivery of time-critical medical items theme comprised the topics of ‘Emergency Response’, ‘Defibrillator and Organ Delivery’, and ‘Search and Rescue’, whilst non-time-critical delivery researched the topics of ‘Supply Chain Optimisation’ and ‘Cost-Effectiveness’, ‘Overcoming Remoteness’, and ‘Pandemic Response’. Research on ‘Engineering and Design Considerations’ and ‘Ethical and Social Considerations’ cut across both research themes. We undertook further analysis to assess research topic alignment and identify knowledge gaps. We found that efforts are needed to establish a more standardised terminology for better alignment across the two emerging research themes. Future studies should focus on evaluating the impact of drone delivery on patient health using systematic methods. Additionally, exploring the economic viability of drone-based health services and addressing regulatory barriers are crucial for efficient and effective drone deployment in healthcare delivery systems.

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Application of artificial intelligence in triage in emergencies and disasters: a systematic review

Tahernejad,

Sahebi,

Abadi

et al. 2024

BMC Public Health

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Introduction and objective Modern and intelligent triage systems are used today due to the growing trend of disasters and emergencies worldwide and the increase in the number of injured people facing the challenge of using traditional triage methods. The main objective of this study is to investigate the application of artificial intelligence and Technology in the triage of patients injured by disasters and emergencies and the challenges of the implementation of intelligent triage systems. Method The present study is a systematic review and follows PRISMA guidelines. The protocol of this study was registered in PROSPERO with the code CRD42023471415. To find relevant studies, the databases PubMed, Scopus and Web of Science (ISI) were searched without a time limit until September 2024. The scientific search engine Google Scholar and the references of the final articles were read manually for the final review. Results The search identified 2,630 articles, narrowing down to 19 high-quality studies on AI in triage, which improved patient care through optimized resource management and real-time data transmission. AI algorithms like OpenPose and YOLO enhanced efficiency in mass casualty incidents, while e-triage systems allowed for continuous vital sign monitoring and faster triaging. AI tools demonstrated high accuracy in diagnosing COVID-19 (94.57%). Implementing intelligent triage systems faced challenges such as trust issues, training needs, equipment shortages, and data privacy concerns. Conclusion Developing assessment systems using artificial intelligence enables timely treatment and better resuscitation services for people injured in disasters. For future studies, we recommend designing intelligent triage systems to remove the obstacles in triaging children and disabled people in disasters.

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Unmanned aerial vehicle based intelligent triage system in mass-casualty incidents using 5G and artificial intelligence

Cited by 8 publications

References 37 publications

Emergency medical services preparedness in mass casualty incidents: A qualitative study

Emergency medical services preparedness in mass casualty incidents: A qualitative study

Emerging Research Topics in Drone Healthcare Delivery

Application of artificial intelligence in triage in emergencies and disasters: a systematic review

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