HeartForce’s scientific team in Uzbekistan has collected in-depth data for developing an algorithm to screen for coronary artery disease (CAD). The study has been divided into three phases. In phase 1, we collected a total of 1,530 patients’ data to investigate the ability to use machine learning algorithms to predict the presence of CAD. Most of these patients went through invasive coronary angiography (ICA) which revealed high to severe levels of occlusions.
In phase 2, we successfully collected data from 400 individuals, with low CAD probability to form a control group.
In phase 3, we collected data from patients with mild to medium levels of occlusion to form a more homogenous (balance) database. Phase 3 is still on-going and the data of 145 patients has been collected to date. The data collection process is expected to be completed by the end of January 2023.
The statistical model performed high negative predictive value, suitable for screening coronary artery disease.
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