HeRO Risk Scoring Algorithm

AI-based computational tool for assessing patient risk of adverse cardiac events. Integrates multiple clinical, imaging, and laboratory parameters to generate personalized risk scores. Supports evidence-based decision-making for patient management and treatment planning.

Machine learning algorithm for identifying and stratifying high-risk vascular disease patients. Supports resource allocation and targeted preventive intervention strategies.

Proprietary AI algorithms that continuously classify heartbeats and detect the onset and offset of all cardiac arrhythmias. The system provides real-time analysis with the highest diagnostic yield for detecting ventricular and supraventricular arrhythmias.

Software-based cardiac rhythm analysis system for automated arrhythmia identification and classification. Enhances diagnostic accuracy in cardiac assessment.

A software algorithm that automatically identifies and classifies cardiac arrhythmias from electrocardiogram waveforms. The algorithm alerts clinicians to potentially dangerous rhythm disturbances.

An artificial intelligence algorithm analyzing electrocardiogram waveforms for ST-segment and T-wave changes indicative of myocardial ischemia. The algorithm assists in rapid identification of acute coronary syndrome.

Machine learning software for automated detection and classification of cardiac arrhythmias from ECG data. Analyzes heart rhythm patterns to identify pathological conditions and assist in clinical diagnosis. Compatible with multiple cardiac monitoring devices.

Advanced signal processing algorithm for identifying heartbeat indicators in ECG data with customizable filtering. Reduces false detection rates even with motion artifacts and non-traditional electrode configurations.

ANRISK® is an AI-powered risk assessment solution that predicts the likelihood of brain aneurysm development using routine health check-up data alone. Designed as a pre-screening tool prior to brain vascular imaging such as MRA or CTA, ANRISK® enables safe, fast, and cost-effective identification of high-risk individuals without additional medical procedures. Powered by an AI algorithm trained on approximately 8.8 million person-years of large-scale healthcare data, ANRISK® classifies individuals into five risk categories and generates personalized analytical reports. The results include a standardized risk score, estimated prevalence and incidence, contributing risk factors, and tailored lifestyle guidance. ANRISK® is optimized for use in hospitals, health screening centers, and corporate health programs, supporting a preventive approach to cerebrovascular disease management.

A comprehensive risk assessment and management software system for healthcare environments. It identifies potential risks, anticipates patient safety concerns, and supports preventive measures to improve the care environment and patient outcomes.

AI-based software solution that analyzes 10-second normal sinus rhythm ECG data to predict atrial fibrillation risk and identify patients at potential risk for arrhythmia development. The system provides quantified risk assessment to support clinical decision-making for early detection and preventive management.

AI-powered computational module generating integrated cardiovascular and cerebrovascular risk assessment scores. Combines physiological data interpretation with machine learning to provide comprehensive risk profiling for clinical decision-making.