Filter by input type
Select all
News
Pages
Events
Filter by category
Select all
AI ANALYTICS
Mobile Apps and Internet of Things
Advancement of science
big data
Connected communities
Coronavirus
Courses and training
DIAGNOSIS
Initial Editorial
Editorials
A world in the cloud
Events
Infographics
Artificial Intelligence and Science
IoT Apps
News
Digital platforms
Social networks
Review of scientific publications
Course Summary
Synopsis of essay
Overview of reference frames
Synopsis of recent publications
Use of Digital Platforms
Stanford scientists created a system that predicts immune health through Artificial Intelligence

Scientists and researchers at the Buck Institute for Research on Aging at Stanford University developed iAge, a “clock” that predicts variables and metrics related to longevity.

The Buck Institute for Research on Aging of Stanford University, is a study and research center specializing in biomedical research, aging and age-related diseases. Scientists from one of its research groups have developed an aging clock, which measures the inflammatory load, predicts multiple morbidity, frailty, immune health and cardiovascular aging.

To develop the system age used a system based on Artificial Intelligence trained through a blood immunoma study of 1001 participants. "Standard immune metrics that can be used to identify individuals who are most at risk of developing single or even multiple chronic diseases of aging have been growing rapidly," the researchers explained.

The researchers have explained the importance of biology in their approach, managed to identify a greater number of metrics so that they now have the means to detect dysfunction in organs and act before the patient develops a disease.

Through age It will be possible to know the risk of a person developing various chronic diseases, this through the evaluation of the cumulative physiological damage to their immune system. “All of these people (participants) are healthy according to all available laboratory tests and clinical evaluations, but using iAge we were able to predict who is likely to have left ventricular hypertrophy (an enlargement and thickening of the walls of the ventricle chamber). main pumping of the heart) and vascular dysfunction,” they explained.

Related Content

Secured By miniOrange