The startup has developed a clinical decision support system that leverages artificial intelligence and real-time data from ventilators to identify early signs of complications such as pneumonia and sepsis. This technology aims to enhance patient outcomes in intensive care by providing actionable insights to medical staff, ultimately reducing healthcare costs and alleviating staff burnout.
Funding
$830K raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
ICU clinicians face challenges in optimizing mechanical ventilation due to the complexity of ventilator data and the need for continuous monitoring. Delays in identifying complications like pneumonia, sepsis, ARDS, or barotrauma can lead to increased mortality rates and longer ICU stays. Traditional methods often lack the ability to provide timely, personalized treatment adjustments.
Solution
Deep Breath offers a remote monitoring and AI-based clinical decision support system designed to optimize mechanical lung ventilation in the ICU. The platform processes real-time data from ventilators and patient data management systems (PDMS) to detect early signs of complications and forecast unwanted events. AI algorithms analyze breath curves and the overall clinical picture to provide explainable and trustworthy recommendations for treatment. By enhancing traditional ventilation, Deep Breath aims to reduce mortality rates, shorten ICU stays, and increase hospital capacity while reducing medical staff workload.
Target Audience
The primary target audience includes clinicians in intensive care units, clinical researchers, and medical device manufacturers seeking to enhance their ventilator technology with AI-driven insights.
Features
- Real-time remote monitoring of ventilator data.
- AI-powered detection of early signs of complications such as pneumonia, sepsis, ARDS, and barotrauma.
- Predictive algorithms to forecast unwanted events based on patient data.
- Personalized treatment recommendations based on the entire clinical picture.
- Analytics module for collecting, storing, processing, and analyzing breath curves data.
- Integration with existing ventilators and other medical devices like blood gas exchange (BGE) analyzers.
- Automated detection of patient-ventilator asynchrony.
- Compatibility with Hamilton G5/C6, Dräger Evita 500/600/800, and Getinge Servo-U ventilators, with the ability to integrate others.