Management of MASS Casualty via an Artificial Intelligence Based System
We design a decision support framework for the management of mass casualty situations at collection points with a reachback functionality (Management of MASS Casualty via an Artificial Intelligence Based System – MASSAI).
Its scope is to support decision-makers (healthcare personnel and aides) by implementing emergency ultrasound in injury assessment at disaster site using portable ultrasound scanners and offering easy-to-use computer-aided tools for mobile devices. Such framework will help to perform triage and more accurate re-triage of casualties with injuries at thorax and abdomen by suggesting efficient therapeutic decisions and assisting the coordinated evacuation of the injured persons. The proposed decision support framework can be used in disasters caused by terrorism as well as natural phenomena, particularly in countries with high seismic hazard.
project scope
In the NATO MASSAI project we design a decision support framework for the management of mass casualty situations at collection points with a reachback functionality. Its scope is to support decision-makers (healthcare personnel and aides) by implementing emergency ultrasound in injury assessment at disaster site using portable ultrasound scanners and offering easy-to-use computer-aided tools for mobile devices.
Our proposed solution is aimed implementing emergency ultrasound in injury assessment at disaster site using portable ultrasound scanners, and offering easy-to-use computer-aided tools for mobile devices, which will help to perform triage (based on vital signs) and more accurate re-triage of casualties with injuries of thorax and abdomen (taking into account level of urgency determined by emergency ultrasound), will suggest efficient therapeutic decisions (life-threatening injuries and emergency diagnostics), and will assist the coordinated evacuation of the injured persons via an intelligent management cockpit.
The data analysed in the framework of the project has multilayered structure. It is obtained during all stages of casualty management at collection points, from treatment to evacuation: registration, triage, re-triage, life-threatening injuries and transportation.
The proposed decision support framework can be used in disasters caused by terrorism as well as natural phenomena, particularly in countries with high seismic hazard. The idea behind this project is first proposed in (Constantin et al. 2018).
Reference:
Gaindric, Constantin; Cojocaru, Svetlana; Pickl, Stefan; Nistor, Marian Sorin; Secrieru; Iulian; Popcova, Olga (2018) A Concept for a Decision Support Framework for the Management of Complex Mass Casualty Situations at Distribution Points. In Svetlana Cojocaru, Constantin Gaindric, I. Drugus (Eds.): Proceedings of the Conference on Mathematical Foundations of Informatics (MFOI’2018), July 2 - 6, 2018, Chisinau, Republic of Moldova. Conference on Mathematical Foundations of Informatics, pp. 90–102.
Project Partner
Institute for Theoretical Computer Science, Mathematics and Operations Research
Universität der Bundeswehr München, Germany
Prof. Dr. Stefan Pickl
NATO Country Project Director
Dr. Sorin Nistor
Coordinator
Vladimir Andrunachievici Institute of Mathematics and Computer Science
Republic of Moldova
Prof. Dr. habil. Constantin Gaindric
Partner Project Director
Prof. Dr. habil. Svetlana Cojocaru
Prof. Dr. habil. Dmitrii Lozovanu
Olga Popcova
Iulian Secrieru
Elena Guțuleac
Iulian Secrieru
Sergiu Puiu
Mircea Petic
Nichita Degtearev
Grigore Haros
Tudor Bumbu
Olesea Caftanatov
Universitatea de Medicina si Farmacie "Grigore T. Popa" (UMF Iasi), Romania
Univ.Prof.(H) Carmen-Diana Cimpoesu
Partner Project Director
Elena Iftimi
Projects referent
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MD. Paul Nedelea
MD. Catalin Bouros
University of Rijeka (UNIRI), Croatia
Prof. Dr. Dragan Čišić
Co-Director
California State University, Fullerton (CSUF), USA
Dr. Doina Bein
Co-Director