Researchers at The University of Hong Kong have developed a groundbreaking artificial intelligence tool capable of predicting cardiovascular disease risk years before symptoms appear. The new system, called CardiOmicScore, uses a single blood test to estimate a person’s future risk of developing major heart-related diseases.
The study was conducted by scientists at the university’s LKS Faculty of Medicine and published in Nature Communications. Researchers say the technology could transform modern healthcare by helping doctors identify dangerous health conditions up to 15 years before clinical diagnosis.
The AI-powered system can predict the risk of six major cardiovascular conditions, including coronary artery disease, stroke, heart failure, atrial fibrillation, peripheral artery disease, and venous thromboembolism.
AI Technology Detects Disease Before Symptoms Begin
According to researchers, CardiOmicScore is designed to identify hidden biological changes in the body long before visible symptoms appear. Scientists say this early warning system may allow doctors and patients to take preventive action before heart disease develops.
The research team used deep learning technology to analyze complex biological information collected from blood samples. The system combines genomics, metabolomics, and proteomics data to create a detailed picture of a person’s current health condition.
The study examined large-scale population data from the UK Biobank. Researchers analyzed nearly 3,000 circulating proteins and more than 160 metabolites found in blood samples.
These molecular signals provide important information about metabolism, immune system activity, and blood vessel health. Scientists believe the AI model can detect subtle changes linked to future cardiovascular disease risk.
Zhang Qingpeng, Associate Professor in the Department of Pharmacology and Pharmacy at HKUMed, explained that genes show a person’s baseline health risk, while proteins and metabolites reflect the body’s current physical condition.
He said the AI system was designed to decode these biological signals and provide doctors with earlier opportunities for prevention and lifestyle intervention.
Researchers Say Tool Outperforms Traditional Risk Models
Current cardiovascular health assessments usually rely on factors such as age, smoking habits, blood pressure, cholesterol levels, and family history. However, experts say these methods often fail to identify disease risks during the earliest stages.
Traditional polygenic risk scores can estimate inherited genetic risk, but they do not fully reflect the impact of lifestyle, diet, stress, or environmental changes over time.
Researchers said CardiOmicScore performed significantly better than conventional genetic risk models during testing. The system became even more accurate when combined with standard clinical details such as age and gender.
Scientists believe the new technology could improve personalized healthcare by providing more precise and dynamic risk predictions.
Medical experts say the system represents an important step toward precision medicine, where treatment and prevention strategies are tailored to an individual’s unique biological condition.
Future Healthcare Could Shift Toward Prevention
Researchers believe the technology could eventually change how cardiovascular diseases are diagnosed and prevented worldwide. Instead of waiting for symptoms to appear, doctors may soon use AI-powered blood tests to identify risks years in advance.
The study highlights a growing shift in modern healthcare from reactive treatment toward proactive disease prevention.
Scientists say future medical systems could use small blood samples to generate broad cardiovascular risk profiles covering multiple diseases at once.
Professor Zhang explained that the ultimate goal is to prevent disease before it develops rather than treating patients after serious complications emerge.
Experts believe technologies like CardiOmicScore could help reduce healthcare costs, improve patient outcomes, and support healthier lifestyles through earlier medical intervention.
The breakthrough also demonstrates the growing role of artificial intelligence in medical research and disease prediction across global healthcare systems.
