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Intelligent Lung Support for Mechanically Ventilated Patients in the Intensive Care Unit

Project description

AI-driven lung support decisions

A mechanical ventilator is a machine that takes over a person’s breathing during surgery or at the ICU when they cannot breathe on their own. Conventional mechanical ventilation uses a tube in the patient’s mouth or neck. Extracorporeal lung support (ELS) offers an alternative option for supporting breathing as it facilitates blood oxygenation and CO2 removal. The scope of the EU-funded IntelliLung project is to develop an AI support system to optimise mechanical ventilation and ELS decision-making for improved patient care. Importantly, the system will help caregivers explain to patients and their relatives the selected management strategies and provide information on specific diseases. IntelliLung will undertake a multi-centre evaluation of the generated decision support system.

Objective

Invasive mechanical ventilation (MV) is one of the most important and life-saving therapies in the intensive care unit (ICU). In most severe cases, when MV alone is insufficient, extracorporeal lung support (ELS) is initiated. However, MV is recognised as potentially harmful, because inappropriate MV settings in ICU patients are associated with organ damage, contributing to disease burden. Studies revealed that MV is often not properly provided despite clear evidence and guidelines. Furthermore, treatment decisions by the healthcare providers, especially regarding MV and ELS, often remain incomprehensible to the patients and their relatives, since flow of information from caregivers to patients is challenged by a number of factors, including limited time and resources, communication problems as well as patients? capacity to comprehend and memorise information. The project proposed herein aims at clinically validating and extending our IntelliLung Artificial Intelligence Decision Support System (AI-DSS) designed to optimise MV and ELS settings to improve the care of ICU patients, alongside caregiver-patient communication. Thereby, best practice evidence-based MV and ELS within safer therapy corridors for longer periods, faster weaning from MV, and improved survival could be achieved - even in non-experienced hands. Additionally, this project will improve the information flow from caregivers to patients and relatives in the ICU setting. Therefore, we will develop a digital solution that allows automatic generation of an extensive plain-language information package for patients and their relatives, communicating highly individualised information on diseases and knowledge-based disease-management strategies, thus facilitating high-quality current and subsequent care through health literacy empowerment and patient-centredness. We will perform a retrospective and prospective multi-centre study to validate our IntelliLung AI-DSS and the patient information software.

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Keywords

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Programme(s)

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Topic(s)

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Funding Scheme

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HORIZON-RIA - HORIZON Research and Innovation Actions

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Call for proposal

Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.

(opens in new window) HORIZON-HLTH-2021-DISEASE-04

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Coordinator

TECHNISCHE UNIVERSITAET DRESDEN
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 1 797 787,00
Address
HELMHOLTZSTRASSE 10
01069 Dresden
Germany

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Region
Sachsen Dresden Dresden, Kreisfreie Stadt
Activity type
Higher or Secondary Education Establishments
Links
Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

€ 1 797 787,50

Participants (18)

Partners (1)

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