They claim that new artificial intelligence can predict Alzheimer’s up to 7 years before symptoms appear

The treatment of many mental illnesses could undergo a radical change in their diagnosis thanks to the intervention of artificial intelligence (AI). A new study from the University of California at San Francisco (UCSF) indicates that they are working on a method for early diagnosis of Alzheimer’s in older adults.

Alzheimer’s is a brain disorder that gets worse over time. This causes the shrinkage of this organ and the death of brain neurons. It is the most common cause of dementia, a progressive deterioration in memory, thinking, behavior and social skills.

This condition has a significant impact on life quality and functional capacity, not only for those who suffer from it, but also for their closest loved ones.

Scientists have long been trying to discover the biological and predictive factors of Alzheimer’s. The risk of contracting the disease increases with age, and although women tend to live longer than men, this does not fully explain why more women suffer from it than men.

In the near future, testing for signs of the disease could be as simple as check your vision or the level of red blood cells in your blood.

The team of researchers has developed a highly advanced artificial intelligence model that can predict Alzheimer’s up to seven years in advance. Using this method they found that they could identify with a 72% of predictive power that the disease would develop.

“This is a first step towards using artificial intelligence on routine clinical data, not only to identify risk as early as possible, but also to understand the biology behind it,” says Alice Tang, a doctoral student in the lab Sirota of UCSF.

The researchers used the UCSF clinical database, which consists of more than 5 million of patients, to look for co-occurring conditions in patients diagnosed with Alzheimer’s compared to healthy individuals.

The path to move forward

Although it is a rate in which there are many errors and is not perfect, marks a fundamental path to follow in prevention and in the health of those who people who may suffer from this disease in the final stages of their lives.

In addition, it serves to apply preventive measures that can stop the development of the disease or significantly delay it.

“The power of this AI-based approach comes from risk identification based on disease combinations,” says Tang.

To do this, the AI ​​carried out a process of relating with other diseases or disorders that are usually linked to the appearance of this disease.

For example, high blood pressure or cholesterol or vitamin D deficiency are usually very important factors when it comes to manifesting themselves in people who may suffer from this disease in the future.

Others, such as osteoporosis in women or enlarged prostate in men, can also be quite challenging.