Imagine a smart autopilot for breathing machines in the hospital. Instead of doctors guessing the best settings for every unique patient, this AI analyzes data to suggest the safest levels. It also creates simple, digital guides so families can actually understand what is happening to their loved ones.
ICU clinicians struggle to find optimal ventilator settings for individual patients, leading to potential lung injury. Additionally, patients and families often find the complex treatment process incomprehensible due to poor communication.
An AI Decision Support System (AI-DSS) for ventilation optimization, a secure communication middleware for hospital hardware, and a digital plain-language information generator for families.
If you are a manufacturer dealing with static device settings that don't adapt to patients — this project developed an AI-DSS that provides personalized ventilation recommendations. This allows your hardware to move toward intelligent, adaptive therapy corridors.
If you are a software provider dealing with the complexity of ICU data integration — this project developed a secure communication middleware and user interface. This enables the seamless connection of AI algorithms with hospital equipment.
If you are a platform developer dealing with low health literacy in critical care — this project developed a digital solution for automatic generation of plain-language information packages. This improves the flow of information from caregivers to relatives.
Based on available project data, there is no specific pricing or cost model mentioned for the final product.
The project is currently in the multi-centre prospective study phase. Based on available project data, it is being validated in clinical sites but not yet deployed at industrial scale.
Based on available project data, specific licensing terms or patent details are not provided in the summary.
The project period runs from 2022-09-01 to 2027-08-31, indicating the validation process is ongoing.
The project developed a secure communication middleware specifically designed to connect the AI platform with hospital equipment.
The consortium is highly diversified with 20 partners across 9 countries, showing strong international validation. With a 30% industry ratio (6 companies, including 3 SMEs), there is a clear bridge between academic research and commercial application, supported by 7 research entities and 2 universities.
Contact the Technical University of Dresden
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