Imagine trying to solve a puzzle where every patient has different pieces. This project looks at blood, genes, and metabolism to find the hidden patterns that cause long-term illness after Covid. It then builds a smart digital assistant to help doctors predict who will get sick and which treatment will actually work for them.
Physicians lack accurate tools to predict and manage the highly varied symptoms of Long Covid. This leads to inefficient treatment and poor patient outcomes due to a lack of known risk factors and biomarkers.
An AI-informed Long Covid Prediction Support (LCPS) tool and an interactive graphic user interface for clinicians and patients.
If you are a software developer dealing with the lack of standardized diagnostic tools for post-viral syndromes — this project developed a machine learning-informed Long Covid Prediction Support (LCPS) tool that helps clinicians predict clinical manifestations.
If you are a lab company dealing with the need for new diagnostic tests — this project developed high-throughput omics methods to identify predisposing factors and biomarkers that lead to Long Covid Syndrome.
If you are a drug developer dealing with high failure rates in broad patient groups — this project developed a way to cluster patients into groups with specific symptoms to help in the choice of personalized treatments.
Based on available project data, there is no information regarding the pricing or cost of the tool.
The project involves 9 industry partners and 6 SMEs, suggesting a strong focus on industrial applicability and scalability of the AI tools.
Based on available project data, specific licensing terms or patent details are not provided.
The project period runs from 2022-06-01 to 2026-05-31, meaning the final tools will be ready by mid-2026.
The project includes the development of an interactive graphic user interface infographic to communicate recommendations for patient management to clinicians.
The consortium is heavily weighted toward commercial application, with a 64% industry ratio comprising 9 industry partners, including 6 SMEs. This suggests the project is not purely academic, as it balances 4 universities and 1 research institute with a strong contingent of private sector players across 6 countries.
Contact HUS-YHTYMA in Finland
Contact us to track the development of the LCPS tool for your clinic.
