A recent study developed an AI model to determine the age of individuals by analyzing chest radiographs.
By Dr. Priyom Bose, Ph.D.Aug 21 2023Reviewed by Sophia Coveney A recent Lancet Healthy Longevity study developed an AI model, based on deep learning methods, to determine the age of individuals by analyzing their chest radiographs.
Various molecular and phenotypic biomarkers of aging have been identified. For instance, chest radiography has been proposed to be a phenotypic biomarker of aging which is associated with reproducible and minimally invasive methodology. About the study This retrospective, multi-institutional cohort study was divided into two phases. The first phase was associated with biomarker modeling, while the second phase concerned correlation investigation.
Study findings The biomarker modeling phase included a total of 67,099 radiographs from 36,051 healthy participants, whereas the correlation investigation phase included 34,197 radiographs from 34,197 participants. Consistent with previous models, the current biomarker modeling phase generated saliency maps that revealed an elevated accumulation of hot regions in the superior mediastinum with aging. It was observed that lung fields, particularly the lower lung fields, had a significant effect on the accurate estimation of aging through saliency maps.
In this phase, the odd ratios in the cohort of patients with a known disease exhibited a relationship with hyperuricemia, chronic obstructive pulmonary disease, hypertension, lung disease, chronic renal failure, interstitial liver cirrhosis, osteoporosis, and atrial fibrillation.
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