Artificial intelligence-based echocardiography assessment to detect pulmonary hypertension
Automated TRJV measurements on echocardiography were similar to manual measurements, with similarly high and noninferior diagnostic accuracy for PH. These findings demonstrate that automated measurement of TRJV on echocardiography is feasible, accurate and reliable and support the implementation of AI-based approaches to echocardiogram evaluation and diagnostic imaging for PH.
Authors
- Mona Selej (ORCID: https://orcid.org/0000-0001-6409-8594)
- Krit Dwivedi (ORCID: https://orcid.org/0000-0003-4949-4550)
- David Gerard Kiely (ORCID: https://orcid.org/0000-0003-0184-6502)
- Tarik Yardibi
- Athanasios Charalampopoulos (ORCID: https://orcid.org/0000-0001-7281-9507)
- Ahmed Maiter (ORCID: https://orcid.org/0000-0002-4999-2608)
- Mahan Salehi (ORCID: https://orcid.org/0000-0002-4064-4762)
- Michael J. Sharkey (ORCID: https://orcid.org/0000-0001-9851-0014)
- Samer Alabed (ORCID: https://orcid.org/0000-0002-9960-7587)
- Abdul Hameed (ORCID: https://orcid.org/0000-0002-2128-2081)
- Andrew J. Swift
Institutions
- Royal Hallamshire Hospital (GB)
- Janssen (United States) (US)
- University of Sheffield (GB)
Publication Details
- Journal
- ERJ Open Research
- Published
- 2024-11-27
- DOI
- https://doi.org/10.1183/23120541.00592-2024
- Citations
- 8
- Primary Topic
- Pulmonary Hypertension Research and Treatments
- Type
- article
- Field-Weighted Citation Impact
- 3.35
Funders
- Janssen Research and Development