Stud Health Technol Inform. 2024 Aug 22;316:1807-1811. doi: 10.3233/SHTI240782.
ABSTRACT
AIM: Feasibility and reliability evaluation of 5G internet networks (5G IN) upon Artificial Intelligence (AI)/Machine Learning (ML), of telemonitoring and mobile ultrasound (m u/s) in an ambulance car (AC)- integrated in the pre-hospital setting (PS)- to support the Golden Hour Principle (GHP) and optimize outcomes in severe trauma (TRS).
MATERIAL AND METHODS: (PS) organization and care upon (5G IN) high bandwidths (10 GB/s) mobile tele-communication (mTC) experimentation by using the experimental Cobot PROMETHEUS III, pn:100016 by simulation upon six severe trauma clinical cases by ten (N1=10) experts: Four professional rescuers (n1=4), three trauma surgeons (n2=3), a radiologist (n3=1) and two information technology specialists (n4=2) to evaluate feasibility, reliability and clinical usability for instant risk, prognosis and triage computation, decision support and treatment planning by (AI)/(ML) computations in (PS) of (TRS) as well as by performing (PS) (m u/s).
RESULTS: A. Trauma severity scales instant computations by the Cobot PROMETHEUS III, pn 100016) ) based on AI and ML complex algorithms and Cloud Computing, telemonitoring and r showed very high feasibility and reliability upon (5GIN) under specific, technological, training and ergonomic prerequisites B. Measured be-directional (m u/s) images data sharing between (AC) and (ED/TC) showed very high feasibility and reliability upon (5G IN) under specific, technological and ergonomic conditions in (TRS).
CONCLUSION: Integration of (PS) tele-monitoring with (AI)/(ML) and (PS) (m u/s) upon (5GIN) via the Cobot PROMETHEUS III, (pn 100016) in severe (TRS/ES), seems feasible and under specific prerequisites reliable to support the (GHP) and optimize outcomes in adult and pediatric (TRS/ES).
PMID:39176842 | DOI:10.3233/SHTI240782
