Prospects and limitations of artificial intelligence technologies in the decision support system of the disaster medicine service

Abstract

The study aims to analyze the opportunities and limitations of applying artificial intelligence (AI) technologies within the decision support system (DSS) of the All-Russian Disaster Medicine Service (ARDMS). Specifically, the authors cover the issue of lacking specialized databases for AI training, as well as the prospects of utilizing standard ARDMS emergency response algorithms as a foundation for developing domain-adapted large language models (LLMs). An analysis was conducted on the capabilities of AI-powered media monitoring for the early detection of emergency incidents and assessment of their scale.Materials and methods: Regulatory documents governing the activities of the ARDMS were analyzed; an assessment of existing information systems, including those used by the ARDMS, was performed; a comparative analysis of the capabilities of modern LLMs was carried out; data on problems related to operational reporting during the mitigation of medical and sanitary consequences of emergencies was systematized.Results and discussion: Systemic limitations for the application of AI in processing medical data of casualties were identified; an architecture for a hybrid DSS based on a domain-adapted LLM was proposed; the effectiveness of using AI for media monitoring and open-source intelligence analysis was considered.

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