Remote Monitoring, AI, Machine Learning and Mobile Ultrasound Integration upon 5G Internet in the Prehospital Care to Support the Golden Hour Principle and Optimize Outcomes in Severe Trauma and Emergency Surgery...Medical Informatics Europe (MIE) 34th Conference, August 25-29, 2024, Athens, Greece.
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 prehospital setting (PS)- to support the Golden Hour Principle (GHP) and op...
| Publicado en: | Studies in Health Technology & Informatics Vol. 316; pp. 1807 - 1812 |
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| Autores principales: | , |
| Formato: | pictorial proceedings research tables/charts Journal Article |
| Publicado: |
Sage Publications Inc.
2024
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=179286605&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 179286605 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 09269630 U1V jtl: Studies in Health Technology & Informatics issn: 09269630 maglogo: N pubinfo: dt: 2024 vid: 316 pid: 344 pub: Sage Publications Inc. place: Thousand Oaks, California artinfo: ui: 179286605 179286605 179286605 10.3233/SHTI240782 179286605 ppf: 1807 ppct: 5 formats: tig: atl: Remote Monitoring, AI, Machine Learning and Mobile Ultrasound Integration upon 5G Internet in the Prehospital Care to Support the Golden Hour Principle and Optimize Outcomes in Severe Trauma and Emergency Surgery...Medical Informatics Europe (MIE) 34th Conference, August 25-29, 2024, Athens, Greece. aug: au: MAMMAS, Constantinos S. MAMMA, Adamantia S. affil: Program of Excellence 2014-16-Siemens Program for Greece. sug: subj: Remote Consultation Monitoring, Physiologic Artificial Intelligence Machine Learning Internet Access Prehospital Care Outcomes (Health Care) Wounds and Injuries Therapy Severity of Illness Surgery, Operative Methods Emergency Service Reliability Evaluation Ultrasonography Equipment and Supplies Ambulances Automobiles Congresses and Conferences Greece Greece Human Child Adult United States Pilot Studies Telecommunications Experimental Studies Algorithms Cloud Computing Ergonomics Information Technology Surgeons Psychosocial Factors Descriptive Statistics Child: 6-12 years Adult: 19-44 years ab: 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 prehospital 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). pubtype: Academic Journal doctype: pictorial proceedings research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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