Deep Learning-based Estimated Pulmonary Biological Age from Chest CT Images in Healthy Adults: a model development and validation study (Preprint)

Key Points

• Pulmonary biological age estimation reveals a promising new metric for evaluating lung health.
• The deep learning model achieved a correlation of 0.85, indicating strong predictive accuracy in healthy adults.
• Model development involved training on various chest CT images, ensuring robustness and generalizability.
• This approach supports further research on biological aging, potentially impacting early disease detection.