This study, which was carried out by specialists from Japan’s Osaka Metropolitan University, represents a significant advance in the field of medical imaging. It has the potential to improve early disease identification and speed up therapies.
According to recently published research in The Lancet Healthy Longevity journal, a newly developed artificial intelligence (AI) model has demonstrated the ability to identify an individual’s age based on their chest X-ray.
By recognizing the discrepancy between predicted age and chronological age, this AI model has also shown its capability to recognize chronic diseases including hypertension and chronic obstructive pulmonary disease.
This study, which was carried out by specialists from Japan’s Osaka Metropolitan University, represents a significant advance in the field of medical imaging. It has the potential to improve early disease identification and speed up therapies.
Age’s importance in medical science
The importance of study on aging and lifespan is growing as the world’s population ages. People are affected differently by aging, a complex process that is closely linked to many diseases.
The research team emphasized the critical position that chronological age plays in the field of medicine and the importance of its application in determining health status.
According to the study’s principal investigator, Yasuhito Mitsuyama, “Chronological age is one of the most important parameters in medicine. Our findings imply that perceived age based on chest radiography may properly reflect health problems independent of chronological age.
Age estimation abilities of AI
The AI model underwent intensive training utilizing a dataset of over 67,100 chest radiographs collected from 36,051 healthy individuals who had attended health examinations between 2008 and 2021 in order to achieve age prediction.
The age calculated by the AI model and the individuals’ chronological ages were found to be strongly correlated by the researchers.
The AI model’s abilities were improved as it investigated the link between age as determined by the AI and different diseases.
For this, 34,197 chest radiographs from individuals with known illnesses were used in a separate dataset. A large pool of over 101,300 chest X-rays from 70,248 participants at five different universities in Japan were used to refine the model in total.
The function of AI in disease detection
The study’s most startling finding was that there was a strong correlation between chronic diseases like hypertension, hyperuricemia, chronic obstructive pulmonary disease, and hyperuricemia and the difference between a person’s AI-estimated age and their chronological age.
The researchers came to the conclusion that people with higher AI-estimated ages were more likely to suffer from the ailments described above.
Chest X-rays have been proposed by the experts as helpful biomarkers for estimating longevity and aging. Notably, these images give us insights into the intricate workings of internal organs and bones in addition to providing a visual portrayal of interior structures.
