Accepted for/Published in: JMIR Formative Research
Date Submitted: Jan 31, 2022
Date Accepted: Sep 12, 2022
Date Submitted to PubMed: Oct 5, 2022
Risk Assessment of COVID-19 Cases in Emergency Departments and Clinics with the Use of Real-World Data and Artificial Intelligence: Observational Study
ABSTRACT
Background:
The recent COVID-19 pandemic has highlighted the weaknesses of healthcare systems around the world. In the effort to improve the monitoring of cases admitted to Emergency Departments (ED), it has become increasingly necessary to adopt new innovative technological solutions in clinical practice. Currently, continuous monitoring of vital signs is only performed in patients admitted to the Intensive Care Unit (ICU).
Objective:
The study aims to develop a smart system that will dynamically prioritize patients through continuous monitoring of vital signs using a wearable biosensor device and recording of meaningful clinical records, and estimate the likelihood of deterioration of each case using Artificial Intelligence (AI) models.
Methods:
The data for the study will be collected from the ED and COVID-19 inpatient unit of the Hippocration General Hospital of Thessaloniki. The study is carried out in the framework of the COVID-X H2020 project, funded by the European Union. For the training of the neural network, data collection will be performed from COVID-19 cases hospitalized in the respective unit. A wearable biosensor device will be placed on the wrist of each patient, which will record the primary characteristics of the visual signal related to breathing assessment.
Results:
The study will take place over a period of six (6) to eight (8) months.
Conclusions:
The proposed study represents a novel approach of Edge AI method.
Citation
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