LifeSemantics Receives Patent Approval for AI-Based Hypertension Complications Prediction System

LifeSemantics announced on the 30th that the patent registration for the blood pressure prediction AI (artificial intelligence) product ‘CanopyMD HCAI’ model has been approved.

The patent is titled “Bayesian Network-Based Hypertension Complication Prediction System” and pertains to the methodology of an AI model that predicts hypertension complications.

This model, ‘CanopyMD HCAI,’ was developed through the Doctor Answer 2.0 project by the Ministry of Science and ICT and the National IT Industry Promotion Agency (NIPA). It is a medical AI solution that predicts the risk of cardiovascular and cerebrovascular diseases caused by hypertension using demographic data and patients’ clinical data.

First, a Bayesian network is formed with nine measurement variables including age, body mass index (BMI), gender, diastolic blood pressure, and two prediction variables such as the occurrence of complications and types of complications. Then, the system learns this network to predict hypertension complications.

For measuring variables, importance is analyzed using boosting methods (such as XGBoost) or Random Forest among demographic data and over 50 well-known major test data. Subsequently, the top nine variables are selected as measurement variables to predict hypertension complications.

The company explained, “Due to aging, the prevalence of hypertension is increasing,” adding, “If not properly managed, the risk of cardiovascular and cerebrovascular diseases rises, making patient-specific customized treatment plans and follow-up management necessary.”

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