Monitoring and decision support system for mechanical ventilation
Processing a large amount of data, including images, is very laborious
Lack of systematic storage of objective data on the dynamics of treatment
Lack of nurses and sprecialists
Insufficient experience of young professionals and nurses
It is difficult to monitor online what is happening in different wards of different buildings
Processing a large amount of data, including images, is very laborious
Lack of systematic storage of objective data on the dynamics of treatment
Lack of nurses and sprecialists
Insufficient experience of young professionals and nurses
It is difficult to monitor online what is happening in different wards of different buildings
Monitoring of production processes has long been established by the Internet of Things
Machine learning systems predict equipment breakdowns, optimize energy costs and reduce defects
Computer vision systems detect defects, classify products, ensure the safety of objects
Data storage and visualization enables data-driven decision making and retrospective analysis
Monitoring of production processes has long been established by the Internet of Things
Machine learning systems predict equipment breakdowns, optimize energy costs and reduce defects
Computer vision systems detect defects, classify products, ensure the safety of objects
Data storage and visualization enables data-driven decision making and retrospective analysis
In addition to online monitoring, Acrux Deep Breath allows to detect asynchronisms using machine learning algorithms.
Identifying asynchronisms is a non-trivial task that requires highly qualified specialist.
Our algorithms allow us to detect a large number of asynchronisms automatically and collect statistics about them to improve treatment methods
Base screen shows all connected patients and screen of specific patients shows actual data from ventilator and calculated parameters
Screen with asynchronisms shows alerts and history of asynchronisms with possibility to review each PVA
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Base screen shows all connected patients and screen of specific patients shows actual data from ventilator and calculated parameters
online monitoring of all ventilators
via the Internet about important events, regardless of the location of the specialist
for subsequent analysis or solving legal issues
of asynchronisms using machine learning algorithms
Selection of optimal ventilator operating modes using artificial intelligence
Connection takes no more than 5 working days!
Trial period for 30 days
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Dear Albert Flores, thank you for contacting us.
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