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Applying Artificial Intelligence to the 12 Lead ECG for the Diagnosis of Pulmonary Hypertension: an Observational Study
Sponsor: Royal United Hospitals Bath NHS Foundation Trust
Summary
The goal of this observational study is to apply Artificial Intelligence (AI) and machine learning technology to the resting 12-lead electrocardiogram (ECG) and assess whether it can assist doctors in the early diagnosis of Pulmonary Hypertension (PH). Early and accurate diagnosis is an important step for patients with PH. It helps provide effective treatments early which improve prognosis and quality of life. The main questions our study aims to answer are: 1. Can AI technology in the 12-lead ECG accurately predict the presence of PH? 2. Can AI technology in the 12-lead ECG identify specific sub-types of PH? 3. Can AI technology in the 12-lead ECG predict mortality in patients with PH? In this study, the investigators will recruit 12-lead ECGs from consenting participants who have undergone Right heart Catheterisation (RHC) as part of their routine clinical care. AI technology will be applied to these ECGs to assess whether automated technology can predict the presence of PH and it's associated sub-types.
Key Details
Gender
All
Age Range
18 Years - Any
Study Type
OBSERVATIONAL
Enrollment
600
Start Date
2023-10
Completion Date
2027-08
Last Updated
2023-10-05
Healthy Volunteers
Yes
Conditions
Interventions
Artificial Intelligence and Machine Learning technology
Artificial Intelligence describes computer software designed to mimic human cognitive function. Machine learning is a type of artificial intelligence in which the model created is exposed to data, identifies patterns, and recognises relationships between features seen in the data and the 'ground truth'. This technology will be applied to participants ECGs.
Locations (1)
Royal United Hospital Bath NHS Trust
Bath, United Kingdom