Using heart ultrasound scans and patient data to find causes of heart disease
Tests computer tools reading heart ultrasound scans to find heart disease causes.
Plain-language title generated from the registry record
Registry title: Etiological DiagnOsis of caRdiac Diseases Based on echoCardiograpHIc Images and Clinical Data.
Key facts
- Where
- Pierre-Bénite, FranceSee the site
Where in France
- Hopital Lyon SudPierre-Bénite, FranceTaking people
Questions to ask the study team
- How often do I need to come in, and for how long each time?
- Are travel costs paid?
- Can I keep my own doctor?
- What happens if I want to stop?
Trial details
- Who runs it
- Hospices Civils de Lyon
- Trial code
- NCT05942729
- Record updated
- 13 July 2023
- Original description
Research hypothesis - Recent studies have shown that high-dimensional descriptors of the cardiac function can be efficiently exploited to characterize targeted pathologies. In this project, the investigators hypothesize that echocardiograms possess a wealth of information that is currently under-exploited and that, combined with relevant patient data, will allow the development of robust and accurate digital tools for etiological diagnosis.Read full original descriptionShow less
Etiological DiagnOsis of caRdiac Diseases Based on echoCardiograpHIc Images and Clinical Data.
Research hypothesis - Recent studies have shown that high-dimensional descriptors of the cardiac function can be efficiently exploited to characterize targeted pathologies. In this project, the investigators hypothesize that echocardiograms possess a wealth of information that is currently under-exploited and that, combined with relevant patient data, will allow the development of robust and accurate digital tools for etiological diagnosis.
Objectives - Based on key advances recently obtained in image analysis, notably by members of the consortium, the objective of this project is to develop rigorous and explainable cardiac disease prediction models from echocardiography based on the transformer paradigm (AI). The strength of this study lies in the development of a strong AI framework to model the complex interactions between high-quality image-based measurements extracted from echocardiograms and relevant patient data to automatically predict etiological diagnosis of cardiac diseases
Inclusion: Patients with transthoracic echocardiography with satisfactory image quality (sufficient echogenicity).
Exclusion: Minor patients; Patients under curatorship or guardianship.