Is Your Age No Longer a Secret to AI?

What if the concept of "appearing your actual age" pertains not to your facial appearance but to your chest? Scientists from Osaka Metropolitan University have created an advanced artificial intelligence (AI) system that employs chest X-rays to precisely predict a patient's chronological age.

Furthermore, when disparities exist, this system can indicate a potential connection with chronic illnesses. These findings represent a significant advancement in the field of medical imaging, opening doors for enhanced early disease identification and intervention. The study's outcomes are scheduled to be documented in The Lancet Healthy Longevity journal.

Can Chest X-rays be used to Estimate Age using Artificial Intelligence

The team of researchers, led by graduate student Yasuhito Mitsuyama and Dr. Daiju Ueda from the Department of Diagnostic and Interventional Radiology at Osaka Metropolitan University's Graduate School of Medicine, initially developed a deep learning AI model to estimate age based on chest X-rays from healthy individuals.

They subsequently applied this model to X-rays of patients diagnosed with specific diseases to scrutinize the correlation between AI-estimated age and each ailment. Acknowledging that AI trained solely on one dataset is susceptible to overfitting, the scientists amassed data from multiple medical institutions (1^✔ ✔Trusted Source
Artificial Intelligence Estimates Biological Age, Predicts Mortality From a Chest X-ray

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For the development, training, and internal and external testing of the AI model for age estimation, a total of 67,099 chest radiographs were obtained between 2008 and 2021 from 36,051 healthy individuals who underwent health check-ups at three facilities. The developed model showed a correlation coefficient of 0.95 between the AI-estimated age and chronological age. Generally, a correlation coefficient of 0.9 or higher is considered to be very strong.

To validate the usefulness of AI-estimated age using chest radiographs as a biomarker, an additional 34,197 chest radiographs were compiled from 34,197 patients with known diseases from two other institutions.

The results revealed that the difference between AI-estimated age and the patient’s chronological age was positively correlated with a variety of chronic diseases, such as hypertension, hyperuricemia, and chronic obstructive pulmonary disease. In other words, the higher the AI-estimated age compared to the chronological age, the more likely individuals were to have these diseases.

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“Chronological age is one of the most critical factors in medicine,” stated Mr. Mitsuyama. “Our results suggest that chest radiography-based apparent age may accurately reflect health conditions beyond chronological age. We aim to further develop this research and apply it to estimate the severity of chronic diseases, to predict life expectancy, and to forecast possible surgical complications.”

Reference:

1. Artificial Intelligence Estimates Biological Age, Predicts Mortality From a Chest X-ray - (https://advances.massgeneral.org/radiology/journal.aspx?id=2138)

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Source-Eurekalert