Deep Learning-Based Clinical Decision Support System as an Add-on for Non-Invasive Ventilation Devices

  • Dmitrijs Bliznuks (Speaker)
  • Svjatoslavs Kistkins (Co-author)
  • Dana Zariņa (Co-author)
  • Dāvis Freimanis (Co-author)
  • Artis Svaža (Co-author)
  • Sabeļņikovs, O. (Co-author)
  • Valdis Pīrāgs (Co-author)

Activity: Talk or presentation types › Poster presentation

Description

To develop a system for real-time monitoring of OSA, COPD and COVID-19 pneumonia patients. The system should not interfere with the existing NIV system and function as an add-on. The add-on may be used in home care, removing the need for expensive oxygen-rich CPAP or BiLevel devices.. The system consists of a custom-designed printed circuit board that reads vital and respiratory parameters (HR, SpO2, EtCO2) with 4G and WiFi connectivity that allows transmitting the data to the processing center. The retrospective data was obtained from the ‘PhysioNet’ database for training machine learning systems, while the prospective clinical database is still being formed during clinical validation.. We have created a patient respiratory monitoring system, capable of real-time detection of status changes on the NIV equipment. Since the existing ventilation system would not be altered, it was possible to achieve the fail-safe operation of such an add-on prototype.. The proposed clinical decision support system for NIV devices has the potential to improve the monitoring of patients' respiratory conditions and provide timely, accurate treatment recommendations for patients on CPAP treatment. Further clinical research is needed to validate the system and assess its effectiveness in clinical settings.Acknowledgment. Research is funded by the European Regional Development Fund project ”Machine learning-based clinical decision support system for the non-invasive ventilation devices in the treatment of COVID-19 patients” (Nr.1.1.1.1/21/A/082).
Period29 Mar 2023
Event titleRSU International Research Conference 2023: Knowledge for Use in Practice
Event typeConference
OrganiserRīga Stradiņš University
LocationRiga, LatviaShow on map
Degree of RecognitionInternational

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