ABSTRACT
IMACS is an intelligent, interactive cognitive assistant dedicated to cardiac arrest cases in Emergency Medical Service (EMS). EMS providers deal with many cardiac cases. IMACS interacts with EMS providers in real-time and collects vital information from the providers' conversation, including names of interventions, timestamps of interventions, and dosage amount. Throughout the process, IMACS provides necessary reminders and creates a summary report afterward. Using the dynamic behavioral model of two different cardiac arrest recovery protocols, we have developed a critical risk-index based approach to provide time-sensitive feedback and suggest alternatives to the providers in real-time. Our experiments reveal an F1-score of 83% with 300 test cases. A qualitative study also reflects that seven out of ten of the EMS providers rate the system as very helpful in correctly executing cardiac arrest EMS protocols.
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- Sarah Masud Preum, Sile Shu, Jonathan Ting, Vincent Lin, Ronald Williams, John Stankovic, and Homa Alemzadeh. 2018. Towards a cognitive assistant system for emergency response. In 2018 ACM/IEEE 9th International Conference on Cyber-Physical Systems.Google ScholarDigital Library
- M Arif Rahman, Sarah Masud Preum, Ronald D Williams, Homa Alemzadeh, and John A Stankovic. 2020. GRACE: Generating Summary Reports Automatically for Cognitive Assistance in Emergency Response. In AAAI. 13356--13362.Google Scholar
Index Terms
- IMACS - an <u>i</u>nteractive cognitive assistant <u>m</u>odule for <u>c</u>ardiac <u>a</u>rrest cases in emergency medical <u>s</u>ervice: demo abstract
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