Objective
* Background: Emergency care costs are increasing in developed societies, both in rates of emergency department (ED) visits per person and in costs per visit, and are growing faster than other areas of healthcare spending. With limited and unstructured data, ED staff make quick decisions about probabilities for multiple diagnoses and risks. Both underestimation and overestimation of these probabilities lead to increased costs and patient harm. Hence, there is desperate need for clinical decision-support systems in the ED. * Aim: To develop a clinical decision support system for emergency medicine doctors, using sensor data, health records data and patient-reported data, validated in a randomized clinical trial, in order to improve the safety, efficacy and cost-effectiveness of emergency care. * Objectives: We will: Develop machine learning (ML)-powered diagnosis and risk prediction algorithms for common and dangerous conditions based on age, sex, presenting complaints, previous diagnoses, ECGs, and vital parameters; develop and validate a patient-centred technical platform for collecting, storing and sharing patient-reported data and three-dimensional symptom drawings; develop ML-powered diagnosis and risk prediction algorithms for common and dangerous conditions based on patient-reported data and symptom drawings; conduct a large-scale prospective ED data collection for internal and external validation of ML models using a common format for online applications and for further data collection; develop a Bayesian network-powered ED-based clinical decision support system that generates probabilities for diagnoses and 30-day mortality risks and suggestions for the most valuable next step, from data in multiple formats, with visual representation of probabilities, risks and uncertainties and Bayes factors for potential next steps; and conduct a randomized clinical trial investigating the usefulness, effectiveness and safety of the new decision support system.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- social sciences sociology demography mortality
- engineering and technology electrical engineering, electronic engineering, information engineering electronic engineering sensors
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Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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HORIZON.1.1 - European Research Council (ERC)
MAIN PROGRAMME
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Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
HORIZON-ERC - HORIZON ERC Grants
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) ERC-2021-ADG
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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.
751 05 Uppsala
Sweden
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.