Predictive Potential of Retina-Based Biological Age in Assessing Chronic Obstructive Pulmonary Disease Risk.

Qingsheng Peng, Tyler Hyungtaek Rim, Zhi Da Soh, Miao Li Chee, Yih-Chung Tham, Zhuoting Zhu, Simon Nusinovici, Charumathi Sabanayagam, Ah Young Leem, Chan Joo Lee, Byoung Kwon Lee, Sungha Park, Sung Soo Kim, Hyeon Chang Kim, Marco Chak Yan Yu, Tien Yin Wong, Ching-Yu Cheng

Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore. · pubmed

Paper

Abstract

Previously, based on retinal photographs, we developed a deep-learning algorithm to predict biological age (termed, RetiAGE) that was associated with future risks of morbidity and mortality. This study specifically aimed to evaluate the performance of RetiAGE in predicting future risks of chronic obstructive pulmonary disease (COPD).

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Research summary

The paper claims that the RetiAGE algorithm can predict the risk of chronic obstructive pulmonary disease based on biological age derived from retinal photographs. This research is relevant as it explores a novel approach to assess health risks associated with aging, potentially linking biological age to age-related diseases.

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