Periodic Reporting for period 1 - IntelliLung (Intelligent Lung Support for Mechanically Ventilated Patients in the Intensive Care Unit)
Période du rapport: 2022-09-01 au 2024-02-29
Artificial intelligence to help optimize ventilation for intensive care patients
Mechanical ventilation is crucial in ICUs and operating rooms, with improper settings risking organ damage. Various strategies aim to mitigate ventilator-induced lung injury, emphasizing the importance of optimizing mechanical energy delivery and distribution. Artificial intelligence (AI) offers potential benefits in learning from expert practices to enhance lung support and minimize risks.
Invasive mechanical ventilation is critical in ICUs, especially when paired with extracorporeal lung support in severe cases. Despite known risks and established guidelines, mechanical ventilation can be suboptimal, risking organ damage and increasing disease burden. AI can enhance settings by learning from expert variations and patient-specific conditions, aiming to improve outcomes and reduce risks. However, explaining these complex treatments to patients and relatives remains challenging due to communication barriers.
The proposed project aims to validate and enhance the IntelliLung AI-DSS, optimizing mechanical ventilation and extracorporeal support in ICUs. This initiative seeks to establish best practices, extend safer treatment durations, and improve weaning and survival rates. It also focuses on improving communication with patients and relatives by developing a digital tool that provides tailored, understandable information on treatment and disease management. This project will include retrospective and prospective studies to validate IntelliLung AI-DSS and its patient information platform.
Mechanical ventilation is crucial in ICUs and operating rooms, with improper settings risking organ damage. Various strategies aim to mitigate ventilator-induced lung injury, emphasizing the importance of optimizing mechanical energy delivery and distribution. Artificial intelligence (AI) offers potential benefits in learning from expert practices to enhance lung support and minimize risks.
Invasive mechanical ventilation is critical in ICUs, especially when paired with extracorporeal lung support in severe cases. Despite known risks and established guidelines, mechanical ventilation can be suboptimal, risking organ damage and increasing disease burden. AI can enhance settings by learning from expert variations and patient-specific conditions, aiming to improve outcomes and reduce risks. However, explaining these complex treatments to patients and relatives remains challenging due to communication barriers.
The proposed project aims to validate and enhance the IntelliLung AI-DSS, optimizing mechanical ventilation and extracorporeal support in ICUs. This initiative seeks to establish best practices, extend safer treatment durations, and improve weaning and survival rates. It also focuses on improving communication with patients and relatives by developing a digital tool that provides tailored, understandable information on treatment and disease management. This project will include retrospective and prospective studies to validate IntelliLung AI-DSS and its patient information platform.
The IntelliLung project has made notable progress, significantly advancing AI integration in intensive care, particularly for mechanical ventilation support:
WP1: The project's Study Part A, not an EU-classified clinical trial, has been crucial for refining the IntelliLung algorithm before the clinical trial phase. This involved retrospective data analysis across countries, adhering to data protection and laying foundational groundwork for algorithm development. The study, while ongoing, has processed preliminary data and is integrating additional parameters for future ICU application.
WP3: Progress in developing and refining the reinforcement learning algorithm for mechanical ventilation optimization highlights the project's key technical advancement. Detailed performance analysis on benchmark datasets showcases its potential to improve clinical decision-making in ventilation.
WP4: The project has detailed the IntelliLung AI-DSS's architecture, focusing on design, requirements, and ethical alignment with "ethics by design" principles. Establishing KPIs for validation emphasizes the commitment to a reliable and ethical AI-DSS in ICU settings.
WP5: The project's patient-centered care efforts include creating individualized information for patients and relatives using WHI-software. Surveys to gather ICU staff insights on AI-DSS and adapting end-user engagement strategies (like replacing a workshop with a group interview due to recruitment challenges) demonstrate the project's focus on integrating feedback into development.
WP1: The project's Study Part A, not an EU-classified clinical trial, has been crucial for refining the IntelliLung algorithm before the clinical trial phase. This involved retrospective data analysis across countries, adhering to data protection and laying foundational groundwork for algorithm development. The study, while ongoing, has processed preliminary data and is integrating additional parameters for future ICU application.
WP3: Progress in developing and refining the reinforcement learning algorithm for mechanical ventilation optimization highlights the project's key technical advancement. Detailed performance analysis on benchmark datasets showcases its potential to improve clinical decision-making in ventilation.
WP4: The project has detailed the IntelliLung AI-DSS's architecture, focusing on design, requirements, and ethical alignment with "ethics by design" principles. Establishing KPIs for validation emphasizes the commitment to a reliable and ethical AI-DSS in ICU settings.
WP5: The project's patient-centered care efforts include creating individualized information for patients and relatives using WHI-software. Surveys to gather ICU staff insights on AI-DSS and adapting end-user engagement strategies (like replacing a workshop with a group interview due to recruitment challenges) demonstrate the project's focus on integrating feedback into development.
IntelliLung has made significant strides in enhancing, prioritizing unbiased, patient-centered care and utilizing evidence-based protocols. It has developed high-quality, extensive patient datasets from global ICUs, surpassing existing data and enhancing intensive care research.
The IntelliLung AI-DSS is a key innovation, learning from experts to improve care beyond traditional guidelines. It has also streamlined healthcare workflows, positively affecting both providers and patient outcomes.
Future projects will assess IntelliLung AI-DSS's clinical value, comparing it to standard practices and likely attracting further investment. Successful adoption requires educating stakeholders about AI benefits, fostering trust and understanding.
The project boosts health literacy, aiming to improve health outcomes and reduce costs by engaging patients and caregivers in healthcare decisions and providing healthcare professionals with resources to discuss AI treatments.
Additionally, IntelliLung contributes to public health literacy, preparing society for health challenges and enhancing policy support. This work sets new standards in AI-driven, patient-focused care, influencing healthcare delivery, policy, and literacy, with implications for EU healthcare integration and advancement.
The IntelliLung AI-DSS is a key innovation, learning from experts to improve care beyond traditional guidelines. It has also streamlined healthcare workflows, positively affecting both providers and patient outcomes.
Future projects will assess IntelliLung AI-DSS's clinical value, comparing it to standard practices and likely attracting further investment. Successful adoption requires educating stakeholders about AI benefits, fostering trust and understanding.
The project boosts health literacy, aiming to improve health outcomes and reduce costs by engaging patients and caregivers in healthcare decisions and providing healthcare professionals with resources to discuss AI treatments.
Additionally, IntelliLung contributes to public health literacy, preparing society for health challenges and enhancing policy support. This work sets new standards in AI-driven, patient-focused care, influencing healthcare delivery, policy, and literacy, with implications for EU healthcare integration and advancement.