High blood pressure is a major health concern affecting millions of people worldwide. It is closely linked to heart disease, stroke, and kidney problems.
Many people rely on routine doctor visits to check their blood pressure, believing that normal readings mean they are safe. But this is not always the case.
There is a condition called masked hypertension, where a person’s blood pressure appears normal during a clinic visit but is actually high during daily life. Around 10% of people with hypertension fall into this category. Because their readings seem normal, doctors may not suspect a problem, and treatment may be delayed.
The usual way to detect masked hypertension is by using a wearable device that measures blood pressure throughout the day. While this method is accurate, it is not widely used. The equipment can be uncomfortable, costly, and difficult to access, especially in developing regions. As a result, many cases remain undiagnosed.
A new study from the University of Arkansas offers a possible solution. Published in Frontiers in Physiology, the research introduces an artificial intelligence system that can predict masked hypertension using standard health data.
The system was trained using information from a large study in South Africa called African-PREDICT. This study collected data from about 1,200 young adults from diverse backgrounds. Participants wore blood pressure monitors, allowing researchers to clearly identify who had masked hypertension.
Using this data, the AI program learned to recognize patterns linked to the condition. It examined many factors, including age, sex, race, and biological markers found in blood samples. By comparing people with and without masked hypertension, the system identified key differences.
When tested on new data, the AI correctly identified masked hypertension in 83% of cases. This level of accuracy is promising, especially since the system does not require special equipment. It also produced few false alarms, which is important to avoid unnecessary treatments.
One of the strengths of this approach is its ability to process large amounts of information at once. Human doctors typically rely on a limited number of indicators, but AI can analyze many variables together. This allows it to uncover hidden relationships that might otherwise go unnoticed.
In the future, this tool could be built into electronic health record systems. Doctors could use it during routine visits to assess a patient’s risk. This would make screening faster, easier, and more accessible.
However, the study has limitations. The data came from a specific group of young adults, so the model may need further testing in different populations. More research is also needed to ensure the system works well in real-world clinical settings.
Despite these challenges, the findings are encouraging. They suggest that artificial intelligence could help detect hidden health risks and improve patient care. By identifying masked hypertension earlier, doctors could begin treatment sooner and prevent serious complications.
In conclusion, this study highlights the growing role of AI in medicine. While it is not a replacement for doctors, it can support better decision-making and help uncover conditions that are easy to miss.
If you care about high blood pressure, please read studies about unhealthy habits that may increase high blood pressure risk, and drinking green tea could help lower blood pressure.
For more information about high blood pressure, please see recent studies about what to eat or to avoid for high blood pressure, and 12 foods that lower blood pressure.
Source: University of Arkansas.
