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Revolutionizing Emergency Medical Services With AI and Telegram Integration
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Author(s): M. Janakirani (Dr. M.G.R. Educational and Research Institute, India), S. Anandhi (Dr. M.G.R. Educational and Research Institute, India), Tamilselvi Durairajan (Panimalar Engineering College, India), J. Ann Roseela (Dr. M.G.R. Educational and Research Institute, India), B. Swapna (Dr. M.G.R. Educational and Research Institute, India)and R. Kasthuri (Dr. M.G.R. Educational and Research Institute, India)
Copyright: 2025
Pages: 14
Source title:
Humans and Generative AI Tools for Collaborative Intelligence
Source Author(s)/Editor(s): Jingyuan Zhao (University of Toronto, Canada), V. Vinoth Kumar (Vellore Institute of Technology, India), Polinpapilinho F. Katina (University of South Carolina Upstate, USA)and Joseph Richards (California State University, Sacramento, USA)
DOI: 10.4018/979-8-3693-8332-2.ch008
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Abstract
In emergencies, nearly every hospital bed was taken, forcing the collapse of the whole health department. Tragically, many patients lost their lives due to the lack of beds, ventilators, medical intensive care units, or oxygen supplies, as well as the difficulties faced by the ambulance drivers who brought them to the hospital. As a result, they had to wait outside the facility for a long time. The main problem is that there isn't a suitable system linking the surrounding hospitals to analyse the patient's condition simultaneously within the ambulance; hospitals with the necessary equipment should be selected at the appropriate moment. One possible solution to this problem is a system that gathers data about hospitals and medical systems' availability from a centralised server page that links to all nearby hospitals. The system then uses artificial neural networks to analyse the patient's condition with the help of the LSAI48266X AI board.
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